Instructions to use FastVideo/GEN3C-Cosmos-7B-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FastVideo/GEN3C-Cosmos-7B-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("FastVideo/GEN3C-Cosmos-7B-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
Download tokenizer/encoder.jit from FastVideo/GEN3C-Cosmos-7B-Diffusers: direct link, hf CLI and curl.
- Browser
- Download file 86.3 MB
-
https://huggingface.co/FastVideo/GEN3C-Cosmos-7B-Diffusers/resolve/main/tokenizer/encoder.jit
- Command line
-
hf download hf://FastVideo/GEN3C-Cosmos-7B-Diffusers/tokenizer/encoder.jit
-
curl -L -o encoder.jit https://huggingface.co/FastVideo/GEN3C-Cosmos-7B-Diffusers/resolve/main/tokenizer/encoder.jit
86.3 MB
- Xet hash:
- 3a7fede641e48ad5d3df71ca67d01862e5f81c6216e6ebe649ccf2f3d7dbe198
- Size of remote file:
- 86.3 MB
- SHA256:
- 4f08348acac20e1b16283be6a9e3836b54bf556665155989fbb4a9710c20cb7a
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