Instructions to use autotools/ai_video_studio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use autotools/ai_video_studio with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="autotools/ai_video_studio", filename="runtime/Auto Movie Reviewer/models/Phi-3.5-mini-balanced.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 autotools/ai_video_studio 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 autotools/ai_video_studio:Q4_K_M # Run inference directly in the terminal: llama cli -hf autotools/ai_video_studio:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf autotools/ai_video_studio:Q4_K_M # Run inference directly in the terminal: llama cli -hf autotools/ai_video_studio: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 autotools/ai_video_studio:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf autotools/ai_video_studio: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 autotools/ai_video_studio:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf autotools/ai_video_studio:Q4_K_M
Use Docker
docker model run hf.co/autotools/ai_video_studio:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use autotools/ai_video_studio with Ollama:
ollama run hf.co/autotools/ai_video_studio:Q4_K_M
- Unsloth Studio
How to use autotools/ai_video_studio 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 autotools/ai_video_studio 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 autotools/ai_video_studio to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for autotools/ai_video_studio to start chatting
- Atomic Chat new
- Docker Model Runner
How to use autotools/ai_video_studio with Docker Model Runner:
docker model run hf.co/autotools/ai_video_studio:Q4_K_M
- Lemonade
How to use autotools/ai_video_studio with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull autotools/ai_video_studio:Q4_K_M
Run and chat with the model
lemonade run user.ai_video_studio-Q4_K_M
List all available models
lemonade list
| # Community Projects | |
| The following projects are built and maintained by the community. We appreciate all contributions! Note that these projects are not officially supported by the OmniVoice team. | |
| If you have a project you'd like to add, please open a PR. | |
| --- | |
| - **[ComfyUI-OmniVoice-TTS](https://github.com/Saganaki22/ComfyUI-OmniVoice-TTS)** β | |
| ComfyUI custom node for OmniVoice text-to-speech generation. | |
| - **[vLLM-Omni](https://github.com/vllm-project/vllm-omni)** β | |
| A framework for efficient model inference with omni-modality model. Supports OmniVoice serving. | |
| - **[pyVideoTrans](https://github.com/jianchang512/pyvideotrans)** β | |
| Video translation tool with dubbing & subtitles. Supports OmniVoice as a TTS engine. | |
| - **[MLX-Audio](https://github.com/Blaizzy/mlx-audio)** β | |
| TTS, STT, and STS library built on Apple's MLX framework. Supports | |
| OmniVoice among other models for efficient speech processing on Apple Silicon. | |
| - **[RealtimeTTS](https://github.com/KoljaB/RealtimeTTS)** β | |
| Converts text to speech in realtime. Supports OmniVoice as a TTS engine. | |
| - **[TTS-WebUI](https://github.com/rsxdalv/TTS-WebUI)** β | |
| Gradio web UI for multiple TTS models. Supports OmniVoice as one of its backends. | |
| - **[OmniVoice-Studio](https://github.com/debpalash/OmniVoice-Studio)** β | |
| Desktop application for OmniVoice voice generation. | |
| - **[omnivoice-server](https://github.com/maemreyo/omnivoice-server)** β | |
| OpenAI-compatible HTTP server for serving OmniVoice via `/v1/audio/speech`. | |
| Supports voice profiles for persistent cloning, sentence-level streaming, | |
| and optional Bearer auth. | |
| - **[omnivoice-rs](https://github.com/FerrisMind/omnivoice-rs)** β | |
| GPU-first Rust workspace for OmniVoice inference, parity validation, CLI | |
| execution, and an OpenAI-compatible HTTP server built with Candle. | |
| - **[omnivoice-trtllm](https://github.com/tlitech/omnivoice-trtllm)** β | |
| Deploy OmniVoice TTS model using TensorRT-LLM and Triton Inference Server | |
| on Modal, faster than PyTorch. | |
| - **[Auris](https://github.com/nikhilprasanth/Auris)** β | |
| Offline audiobook reader for EPUB, PDF, and TXT with local OmniVoice TTS, character-aware voices, and per-book narrator control. | |