Instructions to use maicomputer/alpaca-native with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maicomputer/alpaca-native with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="maicomputer/alpaca-native")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("maicomputer/alpaca-native") model = AutoModelForCausalLM.from_pretrained("maicomputer/alpaca-native", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use maicomputer/alpaca-native with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "maicomputer/alpaca-native" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "maicomputer/alpaca-native", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/maicomputer/alpaca-native
- SGLang
How to use maicomputer/alpaca-native 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 "maicomputer/alpaca-native" \ --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": "maicomputer/alpaca-native", "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 "maicomputer/alpaca-native" \ --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": "maicomputer/alpaca-native", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use maicomputer/alpaca-native with Docker Model Runner:
docker model run hf.co/maicomputer/alpaca-native
| # Stanford Alpaca | |
| This is a replica of Alpaca by Stanford' tatsu | |
| Trained using the original instructions with a minor modification in FSDP mode | |
| # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) | |
| | Metric | Value | | |
| |-----------------------|---------------------------| | |
| | Avg. | 41.96 | | |
| | ARC (25-shot) | 52.3 | | |
| | HellaSwag (10-shot) | 77.09 | | |
| | MMLU (5-shot) | 41.6 | | |
| | TruthfulQA (0-shot) | 37.58 | | |
| | Winogrande (5-shot) | 69.46 | | |
| | GSM8K (5-shot) | 1.44 | | |
| | DROP (3-shot) | 14.23 | | |