Text Generation
Transformers
Safetensors
mistral
text-generation-inference
8-bit precision
bitsandbytes
Instructions to use NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2") model = AutoModelForCausalLM.from_pretrained("NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2
- SGLang
How to use NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2 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 "NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2" \ --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": "NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2", "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 "NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2" \ --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": "NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2 with Docker Model Runner:
docker model run hf.co/NobodyExistsOnTheInternet/GiftedMistralSysmsgTest2
- Xet hash:
- 20b5f2f3216b114637b1603aeb729c1312dfca4f47385aa4c3e49223b4751095
- Size of remote file:
- 860 MB
- SHA256:
- 9474db6e3f583d4f65f9cf8b1120b59b219f4b86a33640f0fdbfa623bc6860de
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.