Image-to-Video
Diffusers
Safetensors
English
LTX2Pipeline
text-to-video
ltx-2
ltx-2-3
ltx-video
lightricks
Instructions to use CalamitousFelicitousness/LTX-2.3-dev-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CalamitousFelicitousness/LTX-2.3-dev-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CalamitousFelicitousness/LTX-2.3-dev-Diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
fix(text_encoder): remove orphaned index, update generation_config
Browse files
text_encoder/diffusion_pytorch_model.safetensors.index.json
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text_encoder/generation_config.json
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{
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-
"bos_token_id": 2,
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"cache_implementation": "hybrid",
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"do_sample": true,
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"eos_token_id": [
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1,
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106
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],
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"pad_token_id": 0,
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"top_k": 64,
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"top_p": 0.95,
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"transformers_version": "4.
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}
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{
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"cache_implementation": "hybrid",
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"do_sample": true,
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"eos_token_id": [
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1,
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106
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],
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"top_k": 64,
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"top_p": 0.95,
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+
"transformers_version": "4.57.3"
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}
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