Text-to-Speech
Diffusers
Safetensors
GGUF
docker
comfyui
talking-face
lip-sync
live-avatar
music-generation
image-generation
video-generation
skill-pilot
Instructions to use skill-pilot/media-mcp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use skill-pilot/media-mcp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("skill-pilot/media-mcp", 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
Upload README.md with huggingface_hub
Browse files
README.md
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You can use the services until the downloading process is completed. The models will be stored in the `/home/ubuntu/workspace/models` directory inside the container.
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For how to use the media mcp server, please check at https://skill-pilot.ai, and find
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The image is built on runpod/pytorch:2.4.0-py3.11-cuda12.4.1-devel-ubuntu22.04, ensuring compatibility with a wide range of NVIDIA GPUs and CUDA versions.
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You can use the services until the downloading process is completed. The models will be stored in the `/home/ubuntu/workspace/models` directory inside the container.
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For how to use the media mcp server, please check at https://skill-pilot.ai, and find our Discord server invite link at https://skill-pilot.ai and join us for support.
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The image is built on runpod/pytorch:2.4.0-py3.11-cuda12.4.1-devel-ubuntu22.04, ensuring compatibility with a wide range of NVIDIA GPUs and CUDA versions.
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