Instructions to use Trelis/Llama-2-7b-chat-hf-function-calling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Trelis/Llama-2-7b-chat-hf-function-calling with Transformers:

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

pipe = pipeline("text-generation", model="Trelis/Llama-2-7b-chat-hf-function-calling")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Trelis/Llama-2-7b-chat-hf-function-calling")
model = AutoModelForCausalLM.from_pretrained("Trelis/Llama-2-7b-chat-hf-function-calling", device_map="auto")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Trelis/Llama-2-7b-chat-hf-function-calling with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Trelis/Llama-2-7b-chat-hf-function-calling"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Trelis/Llama-2-7b-chat-hf-function-calling",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Trelis/Llama-2-7b-chat-hf-function-calling

SGLang

How to use Trelis/Llama-2-7b-chat-hf-function-calling 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 "Trelis/Llama-2-7b-chat-hf-function-calling" \
    --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": "Trelis/Llama-2-7b-chat-hf-function-calling",
		"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 "Trelis/Llama-2-7b-chat-hf-function-calling" \
        --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": "Trelis/Llama-2-7b-chat-hf-function-calling",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Trelis/Llama-2-7b-chat-hf-function-calling with Docker Model Runner:
```
docker model run hf.co/Trelis/Llama-2-7b-chat-hf-function-calling
```

RonanMcGovern commited on Aug 22, 2023

Commit

57a6493

1 Parent(s): 9c75415

v2 is live

Browse files

Files changed (1) hide show

README.md +6 -0

README.md CHANGED Viewed

@@ -15,6 +15,12 @@ tags:
 - ggml
 - gptq
 ---
 # fLlama 2 - Function Calling Llama 2
 - fLlama 2 extends the hugging face Llama 2 models with function calling capabilities.

 - ggml
 - gptq
 ---
+# ** v2 is now live **
+LLama 2 with function calling (version 2) has been released and is available [here](https://huggingface.co/Trelis/Llama-2-7b-chat-hf-function-calling-v2).
+~~~
 # fLlama 2 - Function Calling Llama 2
 - fLlama 2 extends the hugging face Llama 2 models with function calling capabilities.