Text Generation
Transformers
Safetensors
mistral
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use nilq/mistral-1L-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nilq/mistral-1L-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nilq/mistral-1L-mini")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("nilq/mistral-1L-mini") model = AutoModelForCausalLM.from_pretrained("nilq/mistral-1L-mini") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use nilq/mistral-1L-mini with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nilq/mistral-1L-mini" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nilq/mistral-1L-mini", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/nilq/mistral-1L-mini
- SGLang
How to use nilq/mistral-1L-mini 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 "nilq/mistral-1L-mini" \ --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": "nilq/mistral-1L-mini", "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 "nilq/mistral-1L-mini" \ --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": "nilq/mistral-1L-mini", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use nilq/mistral-1L-mini with Docker Model Runner:
docker model run hf.co/nilq/mistral-1L-mini
Model.py file ? Train.py file ?
#1
by MartialTerran - opened
I know this mistral-1L-mini model and its tensors is able to be operated based on some larger model script downloadable from somewhere on Huggingface.... But, to run it and finetune it and tinker with it local on my PC I would like to have a standalone model.py script (with no dependencies on Huggingface). Can you make the model.safetensors and its config files work with a standalone mistral-1L-mini _model.py and a mistral-1L-mini _train.py and include these necessary mistral-1L-mini in the mistral-1L-mini files?