model-metadata/model_vram_code · Datasets at AI快站

model_id string	vram float64	scripts list	code_urls list	execution_urls list
inclusionAI/Ling-1T	2,420.73	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"inclusionAI/Ling-1T\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('inclusionAI_Ling-1T_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ling-1T_0.txt')\nexcept Exception as e:\n with open('inclusionAI_Ling-1T_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ling-1T_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ling-1T_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"inclusionAI/Ling-1T\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('inclusionAI_Ling-1T_1.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ling-1T_1.txt')\nexcept Exception as e:\n with open('inclusionAI_Ling-1T_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ling-1T_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ling-1T_1.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ling-1T_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ling-1T_1.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ling-1T_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ling-1T_1.txt" ]
tencent/HunyuanImage-3.0	201	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"tencent/HunyuanImage-3.0\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('tencent_HunyuanImage-3.0_0.txt', 'w') as f:\n f.write('Everything was good in tencent_HunyuanImage-3.0_0.txt')\nexcept Exception as e:\n with open('tencent_HunyuanImage-3.0_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='tencent_HunyuanImage-3.0_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='tencent_HunyuanImage-3.0_0.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/tencent_HunyuanImage-3.0_0.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/tencent_HunyuanImage-3.0_0.txt" ]
Salesforce/CoDA-v0-Instruct	9.84	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"Salesforce/CoDA-v0-Instruct\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('Salesforce_CoDA-v0-Instruct_0.txt', 'w') as f:\n f.write('Everything was good in Salesforce_CoDA-v0-Instruct_0.txt')\nexcept Exception as e:\n with open('Salesforce_CoDA-v0-Instruct_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Salesforce_CoDA-v0-Instruct_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='Salesforce_CoDA-v0-Instruct_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModel\n model = AutoModel.from_pretrained(\"Salesforce/CoDA-v0-Instruct\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('Salesforce_CoDA-v0-Instruct_1.txt', 'w') as f:\n f.write('Everything was good in Salesforce_CoDA-v0-Instruct_1.txt')\nexcept Exception as e:\n with open('Salesforce_CoDA-v0-Instruct_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Salesforce_CoDA-v0-Instruct_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='Salesforce_CoDA-v0-Instruct_1.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/Salesforce_CoDA-v0-Instruct_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/Salesforce_CoDA-v0-Instruct_1.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/Salesforce_CoDA-v0-Instruct_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/Salesforce_CoDA-v0-Instruct_1.txt" ]
inclusionAI/Ring-1T-preview	2,420.73	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"inclusionAI/Ring-1T-preview\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('inclusionAI_Ring-1T-preview_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ring-1T-preview_0.txt')\nexcept Exception as e:\n with open('inclusionAI_Ring-1T-preview_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ring-1T-preview_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ring-1T-preview_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"inclusionAI/Ring-1T-preview\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('inclusionAI_Ring-1T-preview_1.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ring-1T-preview_1.txt')\nexcept Exception as e:\n with open('inclusionAI_Ring-1T-preview_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ring-1T-preview_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ring-1T-preview_1.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ring-1T-preview_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ring-1T-preview_1.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ring-1T-preview_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ring-1T-preview_1.txt" ]
radicalnumerics/RND1-Base-0910	73.93	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"radicalnumerics/RND1-Base-0910\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('radicalnumerics_RND1-Base-0910_0.txt', 'w') as f:\n f.write('Everything was good in radicalnumerics_RND1-Base-0910_0.txt')\nexcept Exception as e:\n with open('radicalnumerics_RND1-Base-0910_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='radicalnumerics_RND1-Base-0910_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='radicalnumerics_RND1-Base-0910_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForMaskedLM\n model = AutoModelForMaskedLM.from_pretrained(\"radicalnumerics/RND1-Base-0910\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('radicalnumerics_RND1-Base-0910_1.txt', 'w') as f:\n f.write('Everything was good in radicalnumerics_RND1-Base-0910_1.txt')\nexcept Exception as e:\n with open('radicalnumerics_RND1-Base-0910_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='radicalnumerics_RND1-Base-0910_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='radicalnumerics_RND1-Base-0910_1.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/radicalnumerics_RND1-Base-0910_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/radicalnumerics_RND1-Base-0910_1.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/radicalnumerics_RND1-Base-0910_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/radicalnumerics_RND1-Base-0910_1.txt" ]
jinaai/jina-reranker-v3	0	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModel\n \n tokenizer = AutoTokenizer.from_pretrained(\"jinaai/jina-reranker-v3\", trust_remote_code=True)\n model = AutoModel.from_pretrained(\"jinaai/jina-reranker-v3\", trust_remote_code=True)\n with open('jinaai_jina-reranker-v3_0.txt', 'w') as f:\n f.write('Everything was good in jinaai_jina-reranker-v3_0.txt')\nexcept Exception as e:\n with open('jinaai_jina-reranker-v3_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='jinaai_jina-reranker-v3_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='jinaai_jina-reranker-v3_0.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/jinaai_jina-reranker-v3_0.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/jinaai_jina-reranker-v3_0.txt" ]
inclusionAI/Ming-UniAudio-16B-A3B	44.25	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('inclusionAI_Ming-UniAudio-16B-A3B_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ming-UniAudio-16B-A3B_0.txt')\nexcept Exception as e:\n with open('inclusionAI_Ming-UniAudio-16B-A3B_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ming-UniAudio-16B-A3B_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ming-UniAudio-16B-A3B_0.txt',\n repo_type='dataset',\n )" ]	[ "DO NOT EXECUTE" ]	[ "WAS NOT EXECUTED" ]
rednote-hilab/dots.ocr	7.36	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # integration status unknown.\n \n # Please clone model and use locally.\n \n # Also feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('rednote-hilab_dots.ocr_0.txt', 'w') as f:\n f.write('Everything was good in rednote-hilab_dots.ocr_0.txt')\nexcept Exception as e:\n with open('rednote-hilab_dots.ocr_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='rednote-hilab_dots.ocr_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='rednote-hilab_dots.ocr_0.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/rednote-hilab_dots.ocr_0.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/rednote-hilab_dots.ocr_0.txt" ]
moondream/moondream3-preview	22.44	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"image-text-to-text\", model=\"moondream/moondream3-preview\", trust_remote_code=True)\n with open('moondream_moondream3-preview_0.txt', 'w') as f:\n f.write('Everything was good in moondream_moondream3-preview_0.txt')\nexcept Exception as e:\n with open('moondream_moondream3-preview_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='moondream_moondream3-preview_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='moondream_moondream3-preview_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"moondream/moondream3-preview\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('moondream_moondream3-preview_1.txt', 'w') as f:\n f.write('Everything was good in moondream_moondream3-preview_1.txt')\nexcept Exception as e:\n with open('moondream_moondream3-preview_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='moondream_moondream3-preview_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='moondream_moondream3-preview_1.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/moondream_moondream3-preview_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/moondream_moondream3-preview_1.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/moondream_moondream3-preview_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/moondream_moondream3-preview_1.txt" ]
microsoft/bitnet-b1.58-2B-4T	2.06	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"microsoft/bitnet-b1.58-2B-4T\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('microsoft_bitnet-b1.58-2B-4T_0.txt', 'w') as f:\n f.write('Everything was good in microsoft_bitnet-b1.58-2B-4T_0.txt')\nexcept Exception as e:\n with open('microsoft_bitnet-b1.58-2B-4T_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='microsoft_bitnet-b1.58-2B-4T_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='microsoft_bitnet-b1.58-2B-4T_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"microsoft/bitnet-b1.58-2B-4T\", trust_remote_code=True)\n model = AutoModelForCausalLM.from_pretrained(\"microsoft/bitnet-b1.58-2B-4T\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n inputs = tokenizer.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('microsoft_bitnet-b1.58-2B-4T_1.txt', 'w') as f:\n f.write('Everything was good in microsoft_bitnet-b1.58-2B-4T_1.txt')\nexcept Exception as e:\n with open('microsoft_bitnet-b1.58-2B-4T_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='microsoft_bitnet-b1.58-2B-4T_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='microsoft_bitnet-b1.58-2B-4T_1.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/microsoft_bitnet-b1.58-2B-4T_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/microsoft_bitnet-b1.58-2B-4T_1.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/microsoft_bitnet-b1.58-2B-4T_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/microsoft_bitnet-b1.58-2B-4T_1.txt" ]
moonshotai/Kimi-K2-Instruct-0905	0	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"moonshotai/Kimi-K2-Instruct-0905\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('moonshotai_Kimi-K2-Instruct-0905_0.txt', 'w') as f:\n f.write('Everything was good in moonshotai_Kimi-K2-Instruct-0905_0.txt')\nexcept Exception as e:\n with open('moonshotai_Kimi-K2-Instruct-0905_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='moonshotai_Kimi-K2-Instruct-0905_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='moonshotai_Kimi-K2-Instruct-0905_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"moonshotai/Kimi-K2-Instruct-0905\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('moonshotai_Kimi-K2-Instruct-0905_1.txt', 'w') as f:\n f.write('Everything was good in moonshotai_Kimi-K2-Instruct-0905_1.txt')\nexcept Exception as e:\n with open('moonshotai_Kimi-K2-Instruct-0905_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='moonshotai_Kimi-K2-Instruct-0905_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='moonshotai_Kimi-K2-Instruct-0905_1.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/moonshotai_Kimi-K2-Instruct-0905_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/moonshotai_Kimi-K2-Instruct-0905_1.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/moonshotai_Kimi-K2-Instruct-0905_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/moonshotai_Kimi-K2-Instruct-0905_1.txt" ]
inclusionAI/Ming-UniVision-16B-A3B	45.52	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForSeq2SeqLM\n model = AutoModelForSeq2SeqLM.from_pretrained(\"inclusionAI/Ming-UniVision-16B-A3B\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('inclusionAI_Ming-UniVision-16B-A3B_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ming-UniVision-16B-A3B_0.txt')\nexcept Exception as e:\n with open('inclusionAI_Ming-UniVision-16B-A3B_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ming-UniVision-16B-A3B_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ming-UniVision-16B-A3B_0.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ming-UniVision-16B-A3B_0.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ming-UniVision-16B-A3B_0.txt" ]
deepseek-ai/DeepSeek-R1	1,657.55	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"deepseek-ai/DeepSeek-R1\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('deepseek-ai_DeepSeek-R1_0.txt', 'w') as f:\n f.write('Everything was good in deepseek-ai_DeepSeek-R1_0.txt')\nexcept Exception as e:\n with open('deepseek-ai_DeepSeek-R1_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='deepseek-ai_DeepSeek-R1_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='deepseek-ai_DeepSeek-R1_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"deepseek-ai/DeepSeek-R1\", trust_remote_code=True)\n model = AutoModelForCausalLM.from_pretrained(\"deepseek-ai/DeepSeek-R1\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n inputs = tokenizer.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('deepseek-ai_DeepSeek-R1_1.txt', 'w') as f:\n f.write('Everything was good in deepseek-ai_DeepSeek-R1_1.txt')\nexcept Exception as e:\n with open('deepseek-ai_DeepSeek-R1_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='deepseek-ai_DeepSeek-R1_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='deepseek-ai_DeepSeek-R1_1.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/deepseek-ai_DeepSeek-R1_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/deepseek-ai_DeepSeek-R1_1.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/deepseek-ai_DeepSeek-R1_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/deepseek-ai_DeepSeek-R1_1.txt" ]
ModernVBERT/modernvbert	1.41	[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # integration status unknown.\n \n # Please clone model and use locally.\n \n # Also feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('ModernVBERT_modernvbert_0.txt', 'w') as f:\n f.write('Everything was good in ModernVBERT_modernvbert_0.txt')\nexcept Exception as e:\n with open('ModernVBERT_modernvbert_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='ModernVBERT_modernvbert_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='ModernVBERT_modernvbert_0.txt',\n repo_type='dataset',\n )" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/ModernVBERT_modernvbert_0.py" ]	[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/ModernVBERT_modernvbert_0.txt" ]

inclusionAI/Ling-1T

2,420.73

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"inclusionAI/Ling-1T\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('inclusionAI_Ling-1T_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ling-1T_0.txt')\nexcept Exception as e:\n with open('inclusionAI_Ling-1T_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ling-1T_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ling-1T_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"inclusionAI/Ling-1T\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('inclusionAI_Ling-1T_1.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ling-1T_1.txt')\nexcept Exception as e:\n with open('inclusionAI_Ling-1T_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ling-1T_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ling-1T_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ling-1T_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ling-1T_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ling-1T_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ling-1T_1.txt" ]

tencent/HunyuanImage-3.0

201

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"tencent/HunyuanImage-3.0\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('tencent_HunyuanImage-3.0_0.txt', 'w') as f:\n f.write('Everything was good in tencent_HunyuanImage-3.0_0.txt')\nexcept Exception as e:\n with open('tencent_HunyuanImage-3.0_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='tencent_HunyuanImage-3.0_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='tencent_HunyuanImage-3.0_0.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/tencent_HunyuanImage-3.0_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/tencent_HunyuanImage-3.0_0.txt" ]

Salesforce/CoDA-v0-Instruct

9.84

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"Salesforce/CoDA-v0-Instruct\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('Salesforce_CoDA-v0-Instruct_0.txt', 'w') as f:\n f.write('Everything was good in Salesforce_CoDA-v0-Instruct_0.txt')\nexcept Exception as e:\n with open('Salesforce_CoDA-v0-Instruct_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Salesforce_CoDA-v0-Instruct_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='Salesforce_CoDA-v0-Instruct_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModel\n model = AutoModel.from_pretrained(\"Salesforce/CoDA-v0-Instruct\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('Salesforce_CoDA-v0-Instruct_1.txt', 'w') as f:\n f.write('Everything was good in Salesforce_CoDA-v0-Instruct_1.txt')\nexcept Exception as e:\n with open('Salesforce_CoDA-v0-Instruct_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Salesforce_CoDA-v0-Instruct_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='Salesforce_CoDA-v0-Instruct_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/Salesforce_CoDA-v0-Instruct_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/Salesforce_CoDA-v0-Instruct_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/Salesforce_CoDA-v0-Instruct_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/Salesforce_CoDA-v0-Instruct_1.txt" ]

inclusionAI/Ring-1T-preview

2,420.73

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"inclusionAI/Ring-1T-preview\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('inclusionAI_Ring-1T-preview_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ring-1T-preview_0.txt')\nexcept Exception as e:\n with open('inclusionAI_Ring-1T-preview_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ring-1T-preview_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ring-1T-preview_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"inclusionAI/Ring-1T-preview\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('inclusionAI_Ring-1T-preview_1.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ring-1T-preview_1.txt')\nexcept Exception as e:\n with open('inclusionAI_Ring-1T-preview_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ring-1T-preview_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ring-1T-preview_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ring-1T-preview_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ring-1T-preview_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ring-1T-preview_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ring-1T-preview_1.txt" ]

radicalnumerics/RND1-Base-0910

73.93

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"radicalnumerics/RND1-Base-0910\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('radicalnumerics_RND1-Base-0910_0.txt', 'w') as f:\n f.write('Everything was good in radicalnumerics_RND1-Base-0910_0.txt')\nexcept Exception as e:\n with open('radicalnumerics_RND1-Base-0910_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='radicalnumerics_RND1-Base-0910_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='radicalnumerics_RND1-Base-0910_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForMaskedLM\n model = AutoModelForMaskedLM.from_pretrained(\"radicalnumerics/RND1-Base-0910\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('radicalnumerics_RND1-Base-0910_1.txt', 'w') as f:\n f.write('Everything was good in radicalnumerics_RND1-Base-0910_1.txt')\nexcept Exception as e:\n with open('radicalnumerics_RND1-Base-0910_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='radicalnumerics_RND1-Base-0910_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='radicalnumerics_RND1-Base-0910_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/radicalnumerics_RND1-Base-0910_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/radicalnumerics_RND1-Base-0910_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/radicalnumerics_RND1-Base-0910_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/radicalnumerics_RND1-Base-0910_1.txt" ]

jinaai/jina-reranker-v3

0

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModel\n \n tokenizer = AutoTokenizer.from_pretrained(\"jinaai/jina-reranker-v3\", trust_remote_code=True)\n model = AutoModel.from_pretrained(\"jinaai/jina-reranker-v3\", trust_remote_code=True)\n with open('jinaai_jina-reranker-v3_0.txt', 'w') as f:\n f.write('Everything was good in jinaai_jina-reranker-v3_0.txt')\nexcept Exception as e:\n with open('jinaai_jina-reranker-v3_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='jinaai_jina-reranker-v3_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='jinaai_jina-reranker-v3_0.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/jinaai_jina-reranker-v3_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/jinaai_jina-reranker-v3_0.txt" ]

inclusionAI/Ming-UniAudio-16B-A3B

44.25

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('inclusionAI_Ming-UniAudio-16B-A3B_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ming-UniAudio-16B-A3B_0.txt')\nexcept Exception as e:\n with open('inclusionAI_Ming-UniAudio-16B-A3B_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ming-UniAudio-16B-A3B_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ming-UniAudio-16B-A3B_0.txt',\n repo_type='dataset',\n )" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

rednote-hilab/dots.ocr

7.36

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # integration status unknown.\n \n # Please clone model and use locally.\n \n # Also feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('rednote-hilab_dots.ocr_0.txt', 'w') as f:\n f.write('Everything was good in rednote-hilab_dots.ocr_0.txt')\nexcept Exception as e:\n with open('rednote-hilab_dots.ocr_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='rednote-hilab_dots.ocr_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='rednote-hilab_dots.ocr_0.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/rednote-hilab_dots.ocr_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/rednote-hilab_dots.ocr_0.txt" ]

moondream/moondream3-preview

22.44

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"image-text-to-text\", model=\"moondream/moondream3-preview\", trust_remote_code=True)\n with open('moondream_moondream3-preview_0.txt', 'w') as f:\n f.write('Everything was good in moondream_moondream3-preview_0.txt')\nexcept Exception as e:\n with open('moondream_moondream3-preview_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='moondream_moondream3-preview_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='moondream_moondream3-preview_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"moondream/moondream3-preview\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('moondream_moondream3-preview_1.txt', 'w') as f:\n f.write('Everything was good in moondream_moondream3-preview_1.txt')\nexcept Exception as e:\n with open('moondream_moondream3-preview_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='moondream_moondream3-preview_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='moondream_moondream3-preview_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/moondream_moondream3-preview_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/moondream_moondream3-preview_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/moondream_moondream3-preview_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/moondream_moondream3-preview_1.txt" ]

microsoft/bitnet-b1.58-2B-4T

2.06

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"microsoft/bitnet-b1.58-2B-4T\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('microsoft_bitnet-b1.58-2B-4T_0.txt', 'w') as f:\n f.write('Everything was good in microsoft_bitnet-b1.58-2B-4T_0.txt')\nexcept Exception as e:\n with open('microsoft_bitnet-b1.58-2B-4T_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='microsoft_bitnet-b1.58-2B-4T_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='microsoft_bitnet-b1.58-2B-4T_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"microsoft/bitnet-b1.58-2B-4T\", trust_remote_code=True)\n model = AutoModelForCausalLM.from_pretrained(\"microsoft/bitnet-b1.58-2B-4T\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n inputs = tokenizer.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('microsoft_bitnet-b1.58-2B-4T_1.txt', 'w') as f:\n f.write('Everything was good in microsoft_bitnet-b1.58-2B-4T_1.txt')\nexcept Exception as e:\n with open('microsoft_bitnet-b1.58-2B-4T_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='microsoft_bitnet-b1.58-2B-4T_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='microsoft_bitnet-b1.58-2B-4T_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/microsoft_bitnet-b1.58-2B-4T_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/microsoft_bitnet-b1.58-2B-4T_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/microsoft_bitnet-b1.58-2B-4T_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/microsoft_bitnet-b1.58-2B-4T_1.txt" ]

moonshotai/Kimi-K2-Instruct-0905

0

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"moonshotai/Kimi-K2-Instruct-0905\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('moonshotai_Kimi-K2-Instruct-0905_0.txt', 'w') as f:\n f.write('Everything was good in moonshotai_Kimi-K2-Instruct-0905_0.txt')\nexcept Exception as e:\n with open('moonshotai_Kimi-K2-Instruct-0905_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='moonshotai_Kimi-K2-Instruct-0905_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='moonshotai_Kimi-K2-Instruct-0905_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"moonshotai/Kimi-K2-Instruct-0905\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('moonshotai_Kimi-K2-Instruct-0905_1.txt', 'w') as f:\n f.write('Everything was good in moonshotai_Kimi-K2-Instruct-0905_1.txt')\nexcept Exception as e:\n with open('moonshotai_Kimi-K2-Instruct-0905_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='moonshotai_Kimi-K2-Instruct-0905_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='moonshotai_Kimi-K2-Instruct-0905_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/moonshotai_Kimi-K2-Instruct-0905_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/moonshotai_Kimi-K2-Instruct-0905_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/moonshotai_Kimi-K2-Instruct-0905_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/moonshotai_Kimi-K2-Instruct-0905_1.txt" ]

inclusionAI/Ming-UniVision-16B-A3B

45.52

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForSeq2SeqLM\n model = AutoModelForSeq2SeqLM.from_pretrained(\"inclusionAI/Ming-UniVision-16B-A3B\", trust_remote_code=True, torch_dtype=\"auto\")\n with open('inclusionAI_Ming-UniVision-16B-A3B_0.txt', 'w') as f:\n f.write('Everything was good in inclusionAI_Ming-UniVision-16B-A3B_0.txt')\nexcept Exception as e:\n with open('inclusionAI_Ming-UniVision-16B-A3B_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_Ming-UniVision-16B-A3B_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='inclusionAI_Ming-UniVision-16B-A3B_0.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/inclusionAI_Ming-UniVision-16B-A3B_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/inclusionAI_Ming-UniVision-16B-A3B_0.txt" ]

deepseek-ai/DeepSeek-R1

1,657.55

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"deepseek-ai/DeepSeek-R1\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('deepseek-ai_DeepSeek-R1_0.txt', 'w') as f:\n f.write('Everything was good in deepseek-ai_DeepSeek-R1_0.txt')\nexcept Exception as e:\n with open('deepseek-ai_DeepSeek-R1_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='deepseek-ai_DeepSeek-R1_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='deepseek-ai_DeepSeek-R1_0.txt',\n repo_type='dataset',\n )", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"deepseek-ai/DeepSeek-R1\", trust_remote_code=True)\n model = AutoModelForCausalLM.from_pretrained(\"deepseek-ai/DeepSeek-R1\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n inputs = tokenizer.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('deepseek-ai_DeepSeek-R1_1.txt', 'w') as f:\n f.write('Everything was good in deepseek-ai_DeepSeek-R1_1.txt')\nexcept Exception as e:\n with open('deepseek-ai_DeepSeek-R1_1.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='deepseek-ai_DeepSeek-R1_1.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='deepseek-ai_DeepSeek-R1_1.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/deepseek-ai_DeepSeek-R1_0.py", "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/deepseek-ai_DeepSeek-R1_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/deepseek-ai_DeepSeek-R1_0.txt", "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/deepseek-ai_DeepSeek-R1_1.txt" ]

ModernVBERT/modernvbert

1.41

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"torch\",\n# \"torchvision\",\n# \"transformers\",\n# \"accelerate\",\n# \"peft\",\n# ]\n# ///\n\ntry:\n # integration status unknown.\n \n # Please clone model and use locally.\n \n # Also feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('ModernVBERT_modernvbert_0.txt', 'w') as f:\n f.write('Everything was good in ModernVBERT_modernvbert_0.txt')\nexcept Exception as e:\n with open('ModernVBERT_modernvbert_0.txt', 'w') as f:\n import traceback\n traceback.print_exc(file=f)\nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='ModernVBERT_modernvbert_0.txt',\n repo_id='model-metadata/custom_code_execution_files',\n path_in_repo='ModernVBERT_modernvbert_0.txt',\n repo_type='dataset',\n )" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_py_files/raw/main/ModernVBERT_modernvbert_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/custom_code_execution_files/raw/main/ModernVBERT_modernvbert_0.txt" ]

Datasets:

model-metadata
/

model_vram_code

Collection including model-metadata/model_vram_code

Important