Instructions to use codellama/CodeLlama-7b-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codellama/CodeLlama-7b-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="codellama/CodeLlama-7b-hf")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("codellama/CodeLlama-7b-hf") model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-hf") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use codellama/CodeLlama-7b-hf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "codellama/CodeLlama-7b-hf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "codellama/CodeLlama-7b-hf", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/codellama/CodeLlama-7b-hf
- SGLang
How to use codellama/CodeLlama-7b-hf 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 "codellama/CodeLlama-7b-hf" \ --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": "codellama/CodeLlama-7b-hf", "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 "codellama/CodeLlama-7b-hf" \ --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": "codellama/CodeLlama-7b-hf", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use codellama/CodeLlama-7b-hf with Docker Model Runner:
docker model run hf.co/codellama/CodeLlama-7b-hf
Model trying to allocate 200.00 GiB
I was trying to get the hidden states from an input batch of 100, each with 128 tokens. My code worked with other models. Could someone give me a hint on why this is happening?
OutOfMemoryError: CUDA out of memory. Tried to allocate 200.00 GiB. GPU 0 has a total capacty of 39.56 GiB of which 30.36 GiB is free. Process 22149 has 9.20 GiB memory in use. Of the allocated memory 8.72 GiB is allocated by PyTorch, and 3.84 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF