Instructions to use codellama/CodeLlama-34b-Python-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use codellama/CodeLlama-34b-Python-hf with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="codellama/CodeLlama-34b-Python-hf")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("codellama/CodeLlama-34b-Python-hf")
model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-34b-Python-hf")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use codellama/CodeLlama-34b-Python-hf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "codellama/CodeLlama-34b-Python-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-34b-Python-hf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/codellama/CodeLlama-34b-Python-hf

SGLang

How to use codellama/CodeLlama-34b-Python-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-34b-Python-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-34b-Python-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-34b-Python-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-34b-Python-hf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use codellama/CodeLlama-34b-Python-hf with Docker Model Runner:
```
docker model run hf.co/codellama/CodeLlama-34b-Python-hf
```

osanseviero commited on Aug 25, 2023

Commit

bf21d95

1 Parent(s): 903aef2

Update README.md

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@@ -7,7 +7,7 @@ tags:
 license: llama2
 ---
 # **Code Llama**
-Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 34 billion parameters. This is the repository for the base 7B version in the Hugging Face Transformers format. This model is designed for general code synthesis and understanding. Links to other models can be found in the index at the bottom.
 |     | Base Model                                                                    | Python                                                                                      | Instruct                                                                                        |
 | --- | ----------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------- |
@@ -26,7 +26,7 @@ Code Llama is a collection of pretrained and fine-tuned generative text models r
 * Code Llama - Python: designed specifically for Python
 * Code Llama - Instruct: for instruction following and safer deployment
-=All variants are available in sizes of 7B, 13B and 34B parameters.
 **This repository contains the base model of 7B parameters.**

 license: llama2
 ---
 # **Code Llama**
+Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 34 billion parameters. This is the repository for the 34B Python specialist version in the Hugging Face Transformers format. This model is designed for general code synthesis and understanding. Links to other models can be found in the index at the bottom.
 |     | Base Model                                                                    | Python                                                                                      | Instruct                                                                                        |
 | --- | ----------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------- |
 * Code Llama - Python: designed specifically for Python
 * Code Llama - Instruct: for instruction following and safer deployment
+All variants are available in sizes of 7B, 13B and 34B parameters.
 **This repository contains the base model of 7B parameters.**