Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,48 @@
+---
+license: apache-2.0
+library_name: diffusers
+pipeline_tag: text-to-video
+tags:
+  - wan
+  - echo-memory
+  - world-model
+  - community-pipeline
+---
+
+# Echo-Memory Diffusers pipeline
+
+Community pipeline that overlays the Echo-Memory `context_k1` row onto official **Wan 2.1 1.3B** Diffusers weights.
+
+- Paper: [arXiv:2606.09803](https://arxiv.org/abs/2606.09803)
+- Code: [Echo-Team-Joy-Future-Academy-JD/Echo-Memory](https://github.com/Echo-Team-Joy-Future-Academy-JD/Echo-Memory)
+- Original keys: [Echo-Team/Echo-Memory](https://huggingface.co/Echo-Team/Echo-Memory) `context_k1/epoch-0.safetensors`
+- Converted transformer: this repo, `context_k1-diffusers/diffusion_pytorch_model.safetensors`
+
+This is **not** the full multi-chunk camera-action / SSM research stack. It is the released DiT fine-tune remapped to Diffusers names (825 / 825 official Wan 1.3B transformer keys).
+
+```python
+import torch
+from diffusers import DiffusionPipeline
+from diffusers.utils import export_to_video
+
+pipe = DiffusionPipeline.from_pretrained(
+    "Wan-AI/Wan2.1-T2V-1.3B-Diffusers",
+    custom_pipeline="Wayne-King/echo-memory-diffusers",
+    torch_dtype=torch.bfloat16,
+    trust_remote_code=True,
+)
+pipe.load_echo_memory_weights()  # remaps Echo-Team/Echo-Memory context_k1 on the fly
+# or: pipe.load_converted_echo_memory_weights()  # already-remapped transformer in this repo
+pipe.to("cuda")
+
+frames = pipe(
+    prompt="A golden retriever running across a sunny green field, cinematic camera follow.",
+    negative_prompt="blurry, static, low quality, deformed",
+    height=480,
+    width=832,
+    num_frames=33,
+    num_inference_steps=30,
+    guidance_scale=5.0,
+).frames[0]
+export_to_video(frames, "echo_memory_context_k1.mp4", fps=16)
+```