Text Generation
Transformers
Safetensors
English
table-understanding
instruction-tuning
replication
tabular-data
Instructions to use dnaihao/phi-3-mini-tablebench with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dnaihao/phi-3-mini-tablebench with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="dnaihao/phi-3-mini-tablebench")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dnaihao/phi-3-mini-tablebench", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use dnaihao/phi-3-mini-tablebench with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dnaihao/phi-3-mini-tablebench" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dnaihao/phi-3-mini-tablebench", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/dnaihao/phi-3-mini-tablebench
- SGLang
How to use dnaihao/phi-3-mini-tablebench 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 "dnaihao/phi-3-mini-tablebench" \ --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": "dnaihao/phi-3-mini-tablebench", "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 "dnaihao/phi-3-mini-tablebench" \ --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": "dnaihao/phi-3-mini-tablebench", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use dnaihao/phi-3-mini-tablebench with Docker Model Runner:
docker model run hf.co/dnaihao/phi-3-mini-tablebench
- Xet hash:
- 1d285f4698f3ad09fe3168a5c293377e6017c2c82e109186a8ffca883a3a6e9f
- Size of remote file:
- 3.62 MB
- SHA256:
- 2923f15e986925cfb5e017bc9acbe2e24add5218d2b44558e1283fe76bb6df04
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