Instructions to use hongyin/mistral-0.5b-40k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hongyin/mistral-0.5b-40k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="hongyin/mistral-0.5b-40k")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("hongyin/mistral-0.5b-40k") model = AutoModelForCausalLM.from_pretrained("hongyin/mistral-0.5b-40k") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use hongyin/mistral-0.5b-40k with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hongyin/mistral-0.5b-40k" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hongyin/mistral-0.5b-40k", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/hongyin/mistral-0.5b-40k
- SGLang
How to use hongyin/mistral-0.5b-40k 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 "hongyin/mistral-0.5b-40k" \ --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": "hongyin/mistral-0.5b-40k", "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 "hongyin/mistral-0.5b-40k" \ --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": "hongyin/mistral-0.5b-40k", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use hongyin/mistral-0.5b-40k with Docker Model Runner:
docker model run hf.co/hongyin/mistral-0.5b-40k
hongyin/mistral-0.5b-40k
I am pleased to introduce to you an English-Chinese bilingual autoregressive language model. This model is trained from scratch and has a unique vocabulary and 50 million parameters based on the Mistral model structure. Our goal is to provide a solution that is computationally cheap and easy to inference. It's important to note that this is a base model, not intended to be used as a chatbot, but rather for alchemy. We look forward to providing you with a practical model product.
Losing weight is the only way to solve all problems
Bibtex entry and citation info
Please cite if you find it helpful.
@article{zhu2023metaaid,
title={MetaAID 2.0: An Extensible Framework for Developing Metaverse Applications via Human-controllable Pre-trained Models},
author={Zhu, Hongyin},
journal={arXiv preprint arXiv:2302.13173},
year={2023}
}
license: other
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