Text Generation
Transformers
PyTorch
Safetensors
English
llama
facebook
meta
llama-2
text-generation-inference
Instructions to use NousResearch/Llama-2-7b-chat-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NousResearch/Llama-2-7b-chat-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="NousResearch/Llama-2-7b-chat-hf")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("NousResearch/Llama-2-7b-chat-hf") model = AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-chat-hf") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use NousResearch/Llama-2-7b-chat-hf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "NousResearch/Llama-2-7b-chat-hf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NousResearch/Llama-2-7b-chat-hf", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/NousResearch/Llama-2-7b-chat-hf
- SGLang
How to use NousResearch/Llama-2-7b-chat-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 "NousResearch/Llama-2-7b-chat-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": "NousResearch/Llama-2-7b-chat-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 "NousResearch/Llama-2-7b-chat-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": "NousResearch/Llama-2-7b-chat-hf", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use NousResearch/Llama-2-7b-chat-hf with Docker Model Runner:
docker model run hf.co/NousResearch/Llama-2-7b-chat-hf
add AIBOM
#14 opened 11 months ago
by
sabato-nocera
llama2 _access
#13 opened about 1 year ago
by
Pankajchaudhary9601
Upload tokenizer
#12 opened over 1 year ago
by
dyh2111
Upload LlamaForCausalLM
#11 opened over 1 year ago
by
dyh2111
Interview request: genAI evaluation & documentation
1
#10 opened over 1 year ago
by
evatang
when loaded model config.json not found error occur
#8 opened almost 2 years ago
by
tanzeelabbas
Difference between Llama-2-chat-hf and Llama-2-hf
1
#5 opened over 2 years ago
by
JamesSand20
A fine tuned model can’t answer questions from the dataset
1
#4 opened over 2 years ago
by
celsowm
[AUTOMATED] Model Memory Requirements
#3 opened over 2 years ago
by
model-sizer-bot
Need dataset format for fine-tune
3
#2 opened over 2 years ago
by
deepak1197