Instructions to use Rin247/LTX-2.5-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Rin247/LTX-2.5-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("Rin247/LTX-2.5-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
Upload diffusion_decoder/config.json with huggingface_hub
Browse files
diffusion_decoder/config.json
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{
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"_class_name": "LTX2VideoDiffusionDecoderModel",
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"_diffusers_version": "0.40.0.dev0",
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"decoder_head_dim": 64,
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"decoder_model_output_type": "x0",
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"decoder_num_inference_steps": 1,
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"decoder_stage5_kernel": [
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],
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"decoder_stage_channels": [
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2048,
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1024,
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512,
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512,
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256
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],
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"decoder_stage_depths": [
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4,
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],
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"decoder_stage_kernels": [
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],
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"decoder_t_emb_dim": 384,
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"decoder_timestep_scale_multiplier": 1000.0,
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"decoder_upsample_channel_reductions": [
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2,
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2,
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1,
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],
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"decoder_upsample_strides": [
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],
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"latent_channels": 128,
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"out_channels": 3,
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"patch_size": 4,
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"scaling_factor": 1.0,
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"spatial_compression_ratio": 32,
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"temporal_compression_ratio": 8
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}
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