Instructions to use or4cl3ai/Aiden_t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use or4cl3ai/Aiden_t5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="or4cl3ai/Aiden_t5")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("or4cl3ai/Aiden_t5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use or4cl3ai/Aiden_t5 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "or4cl3ai/Aiden_t5" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "or4cl3ai/Aiden_t5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/or4cl3ai/Aiden_t5
- SGLang
How to use or4cl3ai/Aiden_t5 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "or4cl3ai/Aiden_t5" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "or4cl3ai/Aiden_t5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "or4cl3ai/Aiden_t5" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "or4cl3ai/Aiden_t5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use or4cl3ai/Aiden_t5 with Docker Model Runner:
docker model run hf.co/or4cl3ai/Aiden_t5
Librarian Bot: Update Hugging Face dataset ID
#7
by librarian-bot - opened
README.md
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license: openrail
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datasets:
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autoevaluate/autoeval-eval-jeffdshen__inverse_superglue_mixedp1-jeffdshen__inverse-63643c-1665558893
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shirsh10mall/LLM_Instruct_Learning_Project_Preprocessed_Tokenized_Open_Orca_Dataset_Flan_T5
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library_name: transformers
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pipeline_tag: text-generation
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license: openrail
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library_name: transformers
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tags:
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- text-generation-inference
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datasets:
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- irds/codesearchnet
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- giganticode/java-cmpx-v1
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- codeparrot/github-code
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- autoevaluate/autoeval-eval-jeffdshen__inverse_superglue_mixedp1-jeffdshen__inverse-63643c-1665558893
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- bentrevett/multi30k
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- edbeeching/decision_transformer_gym_replay
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- psyche/common_crawl
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- US-Artificial-Intelligence/algemap
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- rombodawg/2XUNCENSORED_alpaca_840k_Evol_USER_ASSIS
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- griffin/chain_of_density
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- shirsh10mall/LLM_Instruct_Learning_Project_Preprocessed_Tokenized_Open_Orca_Dataset_Flan_T5
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- Thaweewat/chain-of-thought-74k-th
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- AlekseyKorshuk/chain-of-thoughts-chatml-deduplicated
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- dair-ai/emotion
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- Amani27/massive_translation_dataset
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- tau/commonsense_qa
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- nlplabtdtu/test-edu-crawl
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- kernelmachine/open-license-corpus
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- BDas/EnglishNLPDataset
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- EnigmaOfTheWorld/b-mc2-sql-create-context
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- HuggingFaceH4/testing_self_instruct_small
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- RUCAIBox/Data-to-text-Generation
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metrics:
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- accuracy
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- bertscore
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- perplexity
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- precision
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pipeline_tag: text-generation
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