Update README.md

README.md

@@ -9,4 +9,79 @@ base_model:
 - circlestone-labs/Anima-Base-v1.0-Diffusers
 base_model_relation: quantized
 library_name: diffusers
----
+---
+For more information (including how to compress models yourself), check out https://huggingface.co/DFloat11 and https://github.com/LeanModels/DFloat11
+
+Feel free to request for other models for compression as well (for either the `diffusers` library, ComfyUI, or any other model), although models that use architectures which are unfamiliar to me might be more difficult.
+
+### How to Use
+
+#### `diffusers`
+
+```python
+import torch
+from diffusers import ModularPipeline, CosmosTransformer3DModel
+from dfloat11 import DFloat11Model
+from transformers.initialization import no_init_weights
+
+with no_init_weights():
+    transformer = CosmosTransformer3DModel.from_config(
+        CosmosTransformer3DModel.load_config(
+            r"circlestone-labs/Anima-Base-v1.0-Diffusers", 
+            subfolder="transformer"
+        ),
+        torch_dtype=torch.bfloat16
+    ).to(torch.bfloat16)
+
+DFloat11Model.from_pretrained(r"mingyi456/Anima-Base-v1.0-DF11-Diffusers", device="cpu", bfloat16_model=transformer)
+
+text_encoder = DFloat11Model.from_pretrained(r"mingyi456/Qwen3-0.6B-Base-DF11", device = "cpu")
+
+pipe = ModularPipeline.from_pretrained(r"circlestone-labs/Anima-Base-v1.0-Diffusers")
+
+pipe.update_components(text_encoder=text_encoder.model)
+pipe.update_components(transformer=transformer)
+
+pipe.load_components(dtype=torch.bfloat16)
+
+pipe.to("cuda")
+
+image = pipe(
+    prompt="masterpiece, best quality, 1girl, solo, city lights",
+    generator=torch.Generator("cpu").manual_seed(114514),
+).images[0]
+```
+
+#### ComfyUI
+Refer to this [model](https://huggingface.co/mingyi456/Anima-DF11-ComfyUI) instead.
+
+### Compression details
+
+This is the `pattern_dict` for compression:
+
+```python
+pattern_dict = {
+    r"transformer_blocks\.\d+": (
+        "norm1.linear_1",
+        "norm1.linear_2",
+        "attn1.to_q",
+        "attn1.to_k",
+        "attn1.to_v",
+        "attn1.to_out.0",
+        "norm2.linear_1",
+        "norm2.linear_2",
+        "attn2.to_q",
+        "attn2.to_k",
+        "attn2.to_v",
+        "attn2.to_out.0",
+        "norm3.linear_1",
+        "norm3.linear_2",
+        "ff.net.0.proj",
+        "ff.net.2"
+    ),
+    r"time_embed\.t_embedder": (
+        "linear_1",
+        "linear_2",
+    )
+}
+```