Instructions to use Richard-ZZZZZ/wm_ltx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Richard-ZZZZZ/wm_ltx with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Richard-ZZZZZ/wm_ltx", 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 checkpoints/text_encoder/tokenizer.json from Richard-ZZZZZ/wm_ltx: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/Richard-ZZZZZ/wm_ltx/resolve/main/checkpoints/text_encoder/tokenizer.json
- Command line
-
hf download hf://Richard-ZZZZZ/wm_ltx/checkpoints/text_encoder/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Richard-ZZZZZ/wm_ltx/resolve/main/checkpoints/text_encoder/tokenizer.json
33.4 MB
- Xet hash:
- 496b40792704534f01e0d0ff91ceea3114c9e7b389e5b286d554c5e4636ff4ba
- Size of remote file:
- 33.4 MB
- SHA256:
- 7d4046bf0505a327dd5a0abbb427ecd4fc82f99c2ceaa170bc61ecde12809b0c
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