Instructions to use codellama/CodeLlama-70b-Instruct-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use codellama/CodeLlama-70b-Instruct-hf with Transformers:

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

pipe = pipeline("text-generation", model="codellama/CodeLlama-70b-Instruct-hf")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("codellama/CodeLlama-70b-Instruct-hf")
model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-70b-Instruct-hf")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use codellama/CodeLlama-70b-Instruct-hf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "codellama/CodeLlama-70b-Instruct-hf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "codellama/CodeLlama-70b-Instruct-hf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/codellama/CodeLlama-70b-Instruct-hf

SGLang

How to use codellama/CodeLlama-70b-Instruct-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-70b-Instruct-hf" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "codellama/CodeLlama-70b-Instruct-hf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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-70b-Instruct-hf" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "codellama/CodeLlama-70b-Instruct-hf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use codellama/CodeLlama-70b-Instruct-hf with Docker Model Runner:
```
docker model run hf.co/codellama/CodeLlama-70b-Instruct-hf
```

osanseviero

Wauplin HF Staff commited on Mar 4, 2024

Commit

b256b38

verified ·

1 Parent(s): 021abaf

Update examples in README to be compatible with soon-to-come ChatWidget (#23)

Browse files

- Update examples in README to be compatible with soon-to-come ChatWidget (6714a7782a0f256d628dfed416acf3eccb29ea82)

Co-authored-by: Lucain Pouget <Wauplin@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +12 -7

README.md CHANGED Viewed

@@ -6,13 +6,18 @@ tags:
 - llama-2
 license: llama2
 widget:
-  - text: |
-      <s>Source: system
-       You are a helpful and honest code assistant <step> Source: user
-       Print a hello world in Python <step> Source: assistant
-      Destination: user
 inference:
   parameters:
     max_new_tokens: 200

 - llama-2
 license: llama2
 widget:
+  - example_title: Hello world (Python)
+    messages:
+    - role: system
+      content: You are a helpful and honest code assistant
+    - role: user
+      content: Print a hello world in Python
+  - example_title: Sum of sublists (Python)
+    messages:
+    - role: system
+      content: You are a helpful and honest code assistant expert in JavaScript. Please, provide all answers to programming questions in JavaScript
+    - role: user
+      content: Write a function that computes the set of sums of all contiguous sublists of a given list.
 inference:
   parameters:
     max_new_tokens: 200