Text Generation
Transformers
Safetensors
phi
trl
sft
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use codegood/Phi-3-mini-YU with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codegood/Phi-3-mini-YU with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="codegood/Phi-3-mini-YU")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("codegood/Phi-3-mini-YU") model = AutoModelForCausalLM.from_pretrained("codegood/Phi-3-mini-YU", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use codegood/Phi-3-mini-YU with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "codegood/Phi-3-mini-YU" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "codegood/Phi-3-mini-YU", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/codegood/Phi-3-mini-YU
- SGLang
How to use codegood/Phi-3-mini-YU 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 "codegood/Phi-3-mini-YU" \ --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": "codegood/Phi-3-mini-YU", "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 "codegood/Phi-3-mini-YU" \ --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": "codegood/Phi-3-mini-YU", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use codegood/Phi-3-mini-YU with Docker Model Runner:
docker model run hf.co/codegood/Phi-3-mini-YU
- Xet hash:
- 610017311e08b4b8b35acddeefcd59eda3b95d22d18c485269aa342cded4c7a4
- Size of remote file:
- 2.35 GB
- SHA256:
- 13cc5cac4a29473e949294a0e1e5b0d739db469d631b69f80a45e5f0cd004385
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.