Instructions to use codellama/CodeLlama-7b-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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
```

What are the <0x00> to <0xFF> in the tokenizer.json

#16

by jiang719 - opened Sep 4, 2023

Discussion

jiang719

Sep 4, 2023

•

edited Sep 4, 2023

What are these tokens in the tokenizer.

If I run this line

tokenizer.convert_ids_to_tokens(tokenizer.encode('int add(int a, int b) {\n    return a + b;\n}'))

It gives me

['<s>', '▁int', '▁add', '(', 'int', '▁a', ',', '▁int', '▁b', ')', '▁{', '<0x0A>', '▁▁▁', '▁return', '▁a', '▁+', '▁b', ';', '<0x0A>', '}']

Looks like <0x0A> is used as the newline. Initially, I thought these tokens are special tokens for hex-decimal values.

Is this supposed to be correct? What the other tokens mean?

ArthurZ

Code Llama org Sep 27, 2023

I think it is the Bytefallback, which converts some tokens (in that case new lines) to unicode representation

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