Add NF4 quantized EchoMimicV3 transformer weights

README.md

@@ -0,0 +1,55 @@
+---
+language:
+- en
+- zh
+tags:
+- human-animation
+- talking-head
+- video-generation
+- nf4
+- quantized
+- echomimic
+base_model: BadToBest/EchoMimicV3
+library_name: diffusers
+license: apache-2.0
+---
+
+# EchoMimicV3 — NF4 Quantized
+
+This is a **NF4 (NormalFloat4) quantized** version of [EchoMimicV3](https://huggingface.co/BadToBest/EchoMimicV3).
+
+## Quantization Details
+
+| Parameter | Value |
+|-----------|-------|
+| Quantization Type | NF4 (NormalFloat4) |
+| Double Quantization | Yes |
+| Compute Dtype | float16 |
+| Library | bitsandbytes |
+| VRAM Reduction | ~65% (5 GB → ~1.7 GB) |
+
+## Usage
+
+```python
+from transformers import BitsAndBytesConfig
+import torch
+
+nf4_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_compute_dtype=torch.float16
+)
+```
+
+## Citation
+
+```bibtex
+@misc{meng2025echomimicv3,
+  title={EchoMimicV3: 1.3B Parameters are All You Need for Unified Multi-Modal and Multi-Task Human Animation},
+  author={Rang Meng, Yan Wang, Weipeng Wu, Ruobing Zheng, Yuming Li, Chenguang Ma},
+  year={2025},
+  eprint={2507.03905},
+  archivePrefix={arXiv}
+}
+```

quantization_config.json

@@ -0,0 +1,10 @@
+{
+  "quant_type": "nf4",
+  "load_in_4bit": true,
+  "bnb_4bit_quant_type": "nf4",
+  "bnb_4bit_use_double_quant": true,
+  "bnb_4bit_compute_dtype": "float16",
+  "quantized_by": "bitsandbytes",
+  "base_model": "BadToBest/EchoMimicV3",
+  "quantization_date": "2025"
+}

transformer/diffusion_pytorch_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c3a7762147d228a55cf5963642c54e89f91070ebb9c8c0795c6f2dca0be6a215
+size 3414540448