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README.md

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+---
+license: apache-2.0
+datasets:
+- lerobot/libero
+base_model:
+- Wan-AI/Wan2.2-TI2V-5B
+---
+
+# Wan2.2-5B-Libero
+
+This repository provides a Wan2.2 TI2V 5B checkpoint finetuned on the full LIBERO dataset for robotics video generation.
+
+## Model Summary
+
+- Base model: `Wan-AI/Wan2.2-TI2V-5B`
+- Finetuning data: full LIBERO training set
+- Training steps: `85000`
+- Learning rate: `1e-5`
+- Video length: `49` frames
+- Frame rate: `10 FPS`
+- Task setting: image-to-video generation for LIBERO-style robot trajectories
+
+## Files
+
+- `checkpoint.safetensors`: finetuned DiT checkpoint
+
+## Intended Use
+
+This checkpoint is intended to be used together with the original Wan2.2 TI2V 5B text encoder, tokenizer, and VAE.
+
+In LightEWM, inference can be launched by keeping the standard `examples/LIBERO/infer_ti2v_5b.yaml` config and overriding the DiT checkpoint path with:
+
+```bash
+bash scripts/infer.sh \
+  --config examples/LIBERO/infer_ti2v_5b.yaml \
+  --dataset-base-path data/libero_i2v_train \
+  --metadata-path data/libero_i2v_train/metadata_dense_prompt.csv \
+  --ckpt checkpoints/Wan2.2-5B-Libero/checkpoint.safetensors
+```
+
+## Notes
+
+- This repository stores only the finetuned DiT weights.
+- The original Wan2.2 TI2V 5B base checkpoint is still required at inference time.

checkpoint.safetensors

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