Update README.md

README.md

@@ -1,3 +1,37 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+---
+
+Use like:
+
+```py
+CACHE_ROOT        = pathlib.Path("qwen-image-int8-quanto ")   # where we store INT8 modules
+TRANSFORMER_DIR   = CACHE_ROOT / "qwen_image_transformer_int8"
+TEXT_ENCODER_DIR  = CACHE_ROOT / "qwen_text_encoder_int8"
+
+def load_quantized_modules(transformer_dir: pathlib.Path, text_encoder_dir: pathlib.Path):
+    """
+    Load quantized modules (we saved them with the exact filenames the loaders expect).
+    """
+    tr = torch.load(str(transformer_dir / 'pytorch_model.bin'), weights_only=False)
+    te = torch.load(str(text_encoder_dir / 'pytorch_model.bin'), weights_only=False)
+    return tr, te
+
+def build_pipe(cls, transformer_dir: pathlib.Path, text_encoder_dir: pathlib.Path):
+    """
+    Build a pipeline of class `cls` by loading the quantized modules from disk.
+    Fresh module instances each time avoids offload-hook/state reuse hangs.
+    """
+    transformer, text_encoder = load_quantized_modules(transformer_dir, text_encoder_dir)
+    pipe = cls.from_pretrained(
+        BASE_MODEL_ID,
+        transformer=transformer,
+        text_encoder=text_encoder,
+        torch_dtype=torch.bfloat16,
+        use_safetensors=True,
+        low_cpu_mem_usage=True,
+    )
+    pipe.enable_model_cpu_offload()
+    pipe.set_progress_bar_config(disable=False)
+    return pipe
+```