Instructions to use autotools/ai_video_studio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

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

ai_video_studio

File size: 397 Bytes

8dae870

from core.cloner import KokoClone

# Initialize the cloner (Auto-downloads models if missing, and auto-detects CPU/GPU)
cloner = KokoClone()

# Generate your cloned audio!
cloner.generate(
    text="Welcome to KokoClone! This is incredibly easy to use.",
    lang="en",
    reference_audio="ss.wav", # Replace with your actual reference audio file
    output_path="english_output.wav"
)