Instructions to use cloudyu/hy3-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use cloudyu/hy3-gguf with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf cloudyu/hy3-gguf # Run inference directly in the terminal: llama cli -hf cloudyu/hy3-gguf
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf cloudyu/hy3-gguf # Run inference directly in the terminal: llama cli -hf cloudyu/hy3-gguf
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf cloudyu/hy3-gguf # Run inference directly in the terminal: ./build/bin/llama cli -hf cloudyu/hy3-gguf
Use Docker
docker model run hf.co/cloudyu/hy3-gguf
- Llama new
- LM Studio
- Jan
- vLLM
How to use cloudyu/hy3-gguf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cloudyu/hy3-gguf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cloudyu/hy3-gguf", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/cloudyu/hy3-gguf
- Ollama
How to use cloudyu/hy3-gguf with Ollama:
ollama run hf.co/cloudyu/hy3-gguf
- Unsloth Desktop
- Docker Model Runner
How to use cloudyu/hy3-gguf with Docker Model Runner:
docker model run hf.co/cloudyu/hy3-gguf
- Lemonade
How to use cloudyu/hy3-gguf with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull cloudyu/hy3-gguf
Run and chat with the model
lemonade run user.hy3-gguf-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Update README.md
Browse files
README.md
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@@ -25,7 +25,7 @@ These files were produced by the **[`hy3`](https://github.com/yuhai-china/hy3)**
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converter (`hy3-convert`) and are meant to be run with the **`hy3` inference
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engine**, a from-scratch C/Metal/CUDA implementation.
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# Recommended: `
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The checkpoint is natively top k-8 of MOE, but **we recommend running with `-experts 4`**
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— it activates only the 4 highest-scoring routed experts per token instead of 8,
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converter (`hy3-convert`) and are meant to be run with the **`hy3` inference
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engine**, a from-scratch C/Metal/CUDA implementation.
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# Recommended: `top K experts = 4 instead of 8`
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The checkpoint is natively top k-8 of MOE, but **we recommend running with `-experts 4`**
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— it activates only the 4 highest-scoring routed experts per token instead of 8,
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