Text Generation
Transformers
Safetensors
mistral
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use ugonfor/mistral-7b-4bits with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ugonfor/mistral-7b-4bits with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ugonfor/mistral-7b-4bits")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ugonfor/mistral-7b-4bits") model = AutoModelForCausalLM.from_pretrained("ugonfor/mistral-7b-4bits", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ugonfor/mistral-7b-4bits with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ugonfor/mistral-7b-4bits" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ugonfor/mistral-7b-4bits", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ugonfor/mistral-7b-4bits
- SGLang
How to use ugonfor/mistral-7b-4bits 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 "ugonfor/mistral-7b-4bits" \ --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": "ugonfor/mistral-7b-4bits", "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 "ugonfor/mistral-7b-4bits" \ --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": "ugonfor/mistral-7b-4bits", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ugonfor/mistral-7b-4bits with Docker Model Runner:
docker model run hf.co/ugonfor/mistral-7b-4bits
Download tokenizer.json from ugonfor/mistral-7b-4bits: direct link, hf CLI and curl.
- Browser
- Download file 3.51 MB
-
https://huggingface.co/ugonfor/mistral-7b-4bits/resolve/main/tokenizer.json
- Command line
-
hf download hf://ugonfor/mistral-7b-4bits/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ugonfor/mistral-7b-4bits/resolve/main/tokenizer.json
3.51 MB
File too large to display, you can check the raw version instead.