Text Generation
Transformers
PyTorch
English
code
codegen
Diff Model
causal-lm
code-generation
The Pile
Instructions to use CarperAI/diff-codegen-350m-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CarperAI/diff-codegen-350m-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CarperAI/diff-codegen-350m-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CarperAI/diff-codegen-350m-v1") model = AutoModelForCausalLM.from_pretrained("CarperAI/diff-codegen-350m-v1") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use CarperAI/diff-codegen-350m-v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CarperAI/diff-codegen-350m-v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CarperAI/diff-codegen-350m-v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/CarperAI/diff-codegen-350m-v1
- SGLang
How to use CarperAI/diff-codegen-350m-v1 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 "CarperAI/diff-codegen-350m-v1" \ --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": "CarperAI/diff-codegen-350m-v1", "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 "CarperAI/diff-codegen-350m-v1" \ --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": "CarperAI/diff-codegen-350m-v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use CarperAI/diff-codegen-350m-v1 with Docker Model Runner:
docker model run hf.co/CarperAI/diff-codegen-350m-v1
| { | |
| "_name_or_path": "codegen-350", | |
| "activation_function": "gelu_new", | |
| "architectures": [ | |
| "CodeGenForCausalLM" | |
| ], | |
| "attn_pdrop": 0.0, | |
| "bos_token_id": 1, | |
| "embd_pdrop": 0.0, | |
| "eos_token_id": 50256, | |
| "gradient_checkpointing": false, | |
| "initializer_range": 0.02, | |
| "layer_norm_epsilon": 1e-05, | |
| "model_type": "codegen", | |
| "n_ctx": 2048, | |
| "n_embd": 1024, | |
| "n_head": 16, | |
| "n_inner": null, | |
| "n_layer": 20, | |
| "n_positions": 2048, | |
| "resid_pdrop": 0.0, | |
| "rotary_dim": 32, | |
| "scale_attn_weights": true, | |
| "summary_activation": null, | |
| "summary_first_dropout": 0.1, | |
| "summary_proj_to_labels": true, | |
| "summary_type": "cls_index", | |
| "summary_use_proj": true, | |
| "task_specific_params": { | |
| "text-generation": { | |
| "do_sample": true, | |
| "max_length": 50, | |
| "temperature": 1.0 | |
| } | |
| }, | |
| "tie_word_embeddings": false, | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.22.0.dev0", | |
| "use_cache": true, | |
| "vocab_size": 50295 | |
| } | |