Instructions to use DriiftKing/rvc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use DriiftKing/rvc with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="DriiftKing/rvc", filename="models/onnx_output/Bielik-11B-v3.0-Instruct.Q4_K_M.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use DriiftKing/rvc 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 DriiftKing/rvc:Q4_K_M # Run inference directly in the terminal: llama cli -hf DriiftKing/rvc:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf DriiftKing/rvc:Q4_K_M # Run inference directly in the terminal: llama cli -hf DriiftKing/rvc:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf DriiftKing/rvc:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf DriiftKing/rvc:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf DriiftKing/rvc:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf DriiftKing/rvc:Q4_K_M
Use Docker
docker model run hf.co/DriiftKing/rvc:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use DriiftKing/rvc with Ollama:
ollama run hf.co/DriiftKing/rvc:Q4_K_M
- Unsloth Studio
How to use DriiftKing/rvc with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DriiftKing/rvc to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DriiftKing/rvc to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for DriiftKing/rvc to start chatting
- Atomic Chat new
- Docker Model Runner
How to use DriiftKing/rvc with Docker Model Runner:
docker model run hf.co/DriiftKing/rvc:Q4_K_M
- Lemonade
How to use DriiftKing/rvc with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull DriiftKing/rvc:Q4_K_M
Run and chat with the model
lemonade run user.rvc-Q4_K_M
List all available models
lemonade list
Commit ·
76ebdf9
0
Parent(s):
Duplicate from Jmica/rvc
Browse filesCo-authored-by: Jarod MICA <Jmica@users.noreply.huggingface.co>
- .gitattributes +41 -0
- README.md +3 -0
- assets (rvc_lightwight).zip +3 -0
- deepspeed-0.14.0-cp311-cp311-win_amd64.whl +3 -0
- fairseq-0.12.2-cp310-cp310-win_amd64.whl +3 -0
- fairseq-0.12.2-cp39-cp39-win_amd64.whl +3 -0
- fairseq-0.12.4-cp311-cp311-win_amd64.whl +3 -0
- pyfastmp3decoder-0.0.1-cp311-cp311-win_amd64.whl +0 -0
- rvc.7z +3 -0
- rvc_lightweight.7z +3 -0
- rvc_lightweight.zip +3 -0
.gitattributes
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README.md
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---
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license: mit
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assets (rvc_lightwight).zip
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