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
Load model fail
Get Error
OSError: Unable to load weights from pytorch checkpoint file for '/mnt/bd/fazzie-data/models/CodeLlama-7b-hf/pytorch_model-00001-of-00002.bin' at '/mnt/bd/fazzie-data/models/CodeLlama-7b-hf/pytorch_model-00001-of-00002.bin'. If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True.
Here is the code
from transformers import AutoTokenizer, AutoModelForCausalLM
import transformers
import torch
model = "./models/CodeLlama-7b-hf"
tokenizer = AutoTokenizer.from_pretrained(model)
model = AutoModelForCausalLM.from_pretrained(model)
and I have installed the latest transformers by
pip install git+https://github.com/huggingface/transformers.git@refs/pull/25740/head accelerate
You might have downloaded the repo when it was in an incomplete state, as we are still making changes to it. Does AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-hf") work for you now? It should download the safetensors files we recently uploaded.