Create README.md

README.md

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+---
+base_model:
+- Wan-AI/Wan2.1-T2V-1.3B
+- Wan-AI/Wan2.1-T2V-1.3B-Diffusers
+datasets: finetrainers/crush-smol
+library_name: diffusers
+license: other
+license_link: https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B/blob/main/LICENSE.txt
+widget:
+- text: >-
+    PIKA_CRUSH A large metal cylinder is seen pressing down on a pile of
+    colorful jelly beans, flattening them as if they were under a hydraulic
+    press.
+  output:
+    url: final-3000-0-2-PIKA_CRUSH-A-large-metal-.mp4
+- text: >-
+    PIKA_CRUSH A green cube is being compressed by a hydraulic press, which
+    flattens the object as if it were under a hydraulic press. The press is
+    shown in action, with the cube being squeezed into a smaller shape
+  output:
+    url: final-3000-1-2-PIKA_CRUSH-A-green-cube-i.mp4
+- text: >-
+    PIKA_CRUSH A large metal cylinder is seen pressing down on a pile of Oreo
+    cookies, flattening them as if they were under a hydraulic press.
+  output:
+    url: final-3000-1-2-PIKA_CRUSH-A-large-metal-.mp4
+tags:
+- text-to-video
+- diffusers-training
+- diffusers
+- template:sd-lora
+- wan
+---
+
+<Gallery />
+
+This is a LoRA fine-tune of the [Wan-AI/Wan2.1-T2V-1.3B-Diffusers](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B-Diffusers) model on the
+[finetrainers/crush-smol](https://huggingface.co/datasets/finetrainers/crush-smol) dataset.
+
+Code: https://github.com/a-r-r-o-w/finetrainers
+
+> [!IMPORTANT]
+> This is an experimental checkpoint and its poor generalization is well-known.
+
+Inference code:
+
+```python
+import torch
+from diffusers import WanPipeline
+from diffusers.utils import export_to_video
+
+pipe = WanPipeline.from_pretrained(
+    "Wan-AI/Wan2.1-T2V-1.3B-Diffusers", torch_dtype=torch.bfloat16
+).to("cuda")
+pipe.load_lora_weights("finetrainers/Wan2.1-T2V-1.3B-crush-smol-v0", adapter_name="wan-lora")
+pipe.set_adapters(["wan-lora"], [0.75])
+
+video = pipe("<my-awesome-prompt>").frames[0]
+export_to_video(video, "output.mp4", fps=24)
+```
+
+Training logs are available on WandB [here](https://wandb.ai/aryanvs/finetrainers-wan).