Instructions to use TencentARC/LLaMA-Pro-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TencentARC/LLaMA-Pro-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TencentARC/LLaMA-Pro-8B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TencentARC/LLaMA-Pro-8B") model = AutoModelForCausalLM.from_pretrained("TencentARC/LLaMA-Pro-8B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use TencentARC/LLaMA-Pro-8B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TencentARC/LLaMA-Pro-8B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TencentARC/LLaMA-Pro-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TencentARC/LLaMA-Pro-8B
- SGLang
How to use TencentARC/LLaMA-Pro-8B 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 "TencentARC/LLaMA-Pro-8B" \ --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": "TencentARC/LLaMA-Pro-8B", "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 "TencentARC/LLaMA-Pro-8B" \ --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": "TencentARC/LLaMA-Pro-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TencentARC/LLaMA-Pro-8B with Docker Model Runner:
docker model run hf.co/TencentARC/LLaMA-Pro-8B
Mistral?
#2
by acrastt - opened
Is Mistral and/or Mixtral version planned?
Is Mistral and/or Mixtral version planned?
Of course! We will have a try in the mistral series later. The problem we face is that mistral does not release its pretrain data recipe. We need to select newly added high quality data for our block expansion training in the specific domaiin.