Instructions to use kuleshov/llama-7b-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kuleshov/llama-7b-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="kuleshov/llama-7b-4bit")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("kuleshov/llama-7b-4bit") model = AutoModelForCausalLM.from_pretrained("kuleshov/llama-7b-4bit") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use kuleshov/llama-7b-4bit with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kuleshov/llama-7b-4bit" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kuleshov/llama-7b-4bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/kuleshov/llama-7b-4bit
- SGLang
How to use kuleshov/llama-7b-4bit 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 "kuleshov/llama-7b-4bit" \ --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": "kuleshov/llama-7b-4bit", "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 "kuleshov/llama-7b-4bit" \ --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": "kuleshov/llama-7b-4bit", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use kuleshov/llama-7b-4bit with Docker Model Runner:
docker model run hf.co/kuleshov/llama-7b-4bit
Finetunig the model
#2
by zokica - opened
Hello,
Thanks for the model.
Do you think it is worth to finetune this version (just 4bit), and is there any example in notebook how to do so, even iI think it is pretty similar to GPT2 code for fine tuning.
I guess it is much better to finetune model in fp16 and then quantize it.
Thanks