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README.md

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+---
+pipeline_tag: text-to-video
+library_name: diffusers
+tags:
+- text-to-video
+- image-to-video
+---
+
+Unofficial Diffusers-format weights for https://huggingface.co/Lightricks/LTX-Video (version 0.9.0).
+
+Text-to-Video:
+
+```python
+import torch
+from diffusers import LTXPipeline
+from diffusers.utils import export_to_video
+
+pipe = LTXPipeline.from_pretrained("a-r-r-o-w/LTX-Video-diffusers", torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+
+prompt = "A woman with long brown hair and light skin smiles at another woman with long blonde hair. The woman with brown hair wears a black jacket and has a small, barely noticeable mole on her right cheek. The camera angle is a close-up, focused on the woman with brown hair's face. The lighting is warm and natural, likely from the setting sun, casting a soft glow on the scene. The scene appears to be real-life footage"
+negative_prompt = "worst quality, inconsistent motion, blurry, jittery, distorted"
+
+video = pipe(
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    width=704,
+    height=480,
+    num_frames=161,
+    num_inference_steps=50,
+).frames[0]
+export_to_video(video, "output.mp4", fps=24)
+```
+
+Image-to-Video:
+
+```python
+import torch
+from diffusers import LTXImageToVideoPipeline
+from diffusers.utils import export_to_video, load_image
+
+pipe = LTXImageToVideoPipeline.from_pretrained("a-r-r-o-w/LTX-Video-diffusers", torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+
+image = load_image(
+    "https://huggingface.co/datasets/a-r-r-o-w/tiny-meme-dataset-captioned/resolve/main/images/8.png"
+)
+prompt = "A young girl stands calmly in the foreground, looking directly at the camera, as a house fire rages in the background. Flames engulf the structure, with smoke billowing into the air. Firefighters in protective gear rush to the scene, a fire truck labeled '38' visible behind them. The girl's neutral expression contrasts sharply with the chaos of the fire, creating a poignant and emotionally charged scene."
+negative_prompt = "worst quality, inconsistent motion, blurry, jittery, distorted"
+
+video = pipe(
+    image=image,
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    width=704,
+    height=480,
+    num_frames=161,
+    num_inference_steps=50,
+).frames[0]
+export_to_video(video, "output.mp4", fps=24)
+```

model_index.json

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+{
+  "_class_name": "LTXPipeline",
+  "_diffusers_version": "0.32.0.dev0",
+  "scheduler": [
+    "diffusers",
+    "FlowMatchEulerDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "T5EncoderModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "T5Tokenizer"
+  ],
+  "transformer": [
+    "diffusers",
+    "LTXTransformer3DModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKLLTX"
+  ]
+}

scheduler/scheduler_config.json

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+{
+  "_class_name": "FlowMatchEulerDiscreteScheduler",
+  "_diffusers_version": "0.32.0.dev0",
+  "base_image_seq_len": 1024,
+  "base_shift": 0.95,
+  "invert_sigmas": false,
+  "max_image_seq_len": 4096,
+  "max_shift": 2.05,
+  "num_train_timesteps": 1000,
+  "shift": 1.0,
+  "shift_terminal": 0.1,
+  "use_beta_sigmas": false,
+  "use_dynamic_shifting": true,
+  "use_exponential_sigmas": false,
+  "use_karras_sigmas": false
+}

text_encoder/config.json

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+{
+  "_name_or_path": "google/t5-v1_1-xxl",
+  "architectures": [
+    "T5EncoderModel"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 10240,
+  "d_kv": 64,
+  "d_model": 4096,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "num_decoder_layers": 24,
+  "num_heads": 64,
+  "num_layers": 24,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.2",
+  "use_cache": true,
+  "vocab_size": 32128
+}

text_encoder/model-00001-of-00004.safetensors

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text_encoder/model-00002-of-00004.safetensors

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text_encoder/model-00003-of-00004.safetensors

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vae/config.json

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+{
+  "_class_name": "AutoencoderKLLTX",
+  "_diffusers_version": "0.32.0.dev0",
+  "block_out_channels": [
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+  "decoder_causal": false,
+  "encoder_causal": true,
+  "in_channels": 3,
+  "latent_channels": 128,
+  "layers_per_block": [
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+    3,
+    4
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+  "out_channels": 3,
+  "patch_size": 4,
+  "patch_size_t": 1,
+  "resnet_norm_eps": 1e-06,
+  "scaling_factor": 1.0,
+  "spatio_temporal_scaling": [
+    true,
+    true,
+    true,
+    false
+  ]
+}

vae/diffusion_pytorch_model.safetensors

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