Instructions to use oxide-lab/LTX-Video-0.9.5-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use oxide-lab/LTX-Video-0.9.5-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("oxide-lab/LTX-Video-0.9.5-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use oxide-lab/LTX-Video-0.9.5-diffusers 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 oxide-lab/LTX-Video-0.9.5-diffusers:Q5_K_M # Run inference directly in the terminal: llama cli -hf oxide-lab/LTX-Video-0.9.5-diffusers:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf oxide-lab/LTX-Video-0.9.5-diffusers:Q5_K_M # Run inference directly in the terminal: llama cli -hf oxide-lab/LTX-Video-0.9.5-diffusers:Q5_K_M
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 oxide-lab/LTX-Video-0.9.5-diffusers:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf oxide-lab/LTX-Video-0.9.5-diffusers:Q5_K_M
Use Docker
docker model run hf.co/oxide-lab/LTX-Video-0.9.5-diffusers:Q5_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use oxide-lab/LTX-Video-0.9.5-diffusers with Ollama:
ollama run hf.co/oxide-lab/LTX-Video-0.9.5-diffusers:Q5_K_M
- Unsloth Desktop
- Docker Model Runner
How to use oxide-lab/LTX-Video-0.9.5-diffusers with Docker Model Runner:
docker model run hf.co/oxide-lab/LTX-Video-0.9.5-diffusers:Q5_K_M
- Lemonade
How to use oxide-lab/LTX-Video-0.9.5-diffusers with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull oxide-lab/LTX-Video-0.9.5-diffusers:Q5_K_M
Run and chat with the model
lemonade run user.LTX-Video-0.9.5-diffusers-Q5_K_M
List all available models
lemonade list
- Atomic Chat
Download vae/diffusion_pytorch_model.safetensors from oxide-lab/LTX-Video-0.9.5-diffusers: direct link, hf CLI and curl.
- Browser
- Download file 2.49 GB
-
https://huggingface.co/oxide-lab/LTX-Video-0.9.5-diffusers/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://oxide-lab/LTX-Video-0.9.5-diffusers/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/oxide-lab/LTX-Video-0.9.5-diffusers/resolve/main/vae/diffusion_pytorch_model.safetensors
2.49 GB
- Xet hash:
- ab61d6148596b037438787268c9889fa0d30053042da4d6e69e94bb993659308
- Size of remote file:
- 2.49 GB
- SHA256:
- 7eb65b16cf8ddfd70ccb1c541384ae49ffd6639d754c6b713a11cb72d097233f
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