Text Generation
Transformers
Safetensors
mistral
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use nilq/mistral-2L-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nilq/mistral-2L-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nilq/mistral-2L-tiny")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("nilq/mistral-2L-tiny") model = AutoModelForCausalLM.from_pretrained("nilq/mistral-2L-tiny") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use nilq/mistral-2L-tiny with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nilq/mistral-2L-tiny" # 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-2L-tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/nilq/mistral-2L-tiny
- SGLang
How to use nilq/mistral-2L-tiny 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-2L-tiny" \ --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-2L-tiny", "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-2L-tiny" \ --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-2L-tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use nilq/mistral-2L-tiny with Docker Model Runner:
docker model run hf.co/nilq/mistral-2L-tiny
mistral-2L-tiny_model.py and mistral-2L-tiny_train.py and mistral-2L-tiny_sample.py
#1
by MartialTerran - opened
Can you please add python scripts.py to enable the evaluator can download and run this model (weights and configs and tokenizer) on his local PC. For example, provide standalone python scripts including mistral-2L-tiny_model.py and mistral-2L-tiny_train.py and mistral-2L-tiny_sample.py Especially, python scripts that do not depend upon Huggingface Libraries? So the evaluator can make changes to the standalone python scripts and evaluate the results.