Upload README.md

README.md

@@ -94,6 +94,35 @@ For usage in ComfyUI, [a single transformer file is provided](https://huggingfac
 
 The model can be easily finetuned using [SimpleTuner](https://github.com/bghira/SimpleTuner) and the `--flux_attention_masked_training` training option **and the model found in [jimmycarter/LibreFlux-SimpleTuner](https://huggingface.co/jimmycarter/LibreFlux-SimpleTuner)**. This is the same model with the custom pipeline removed, which currently interferes with the ability for SimpleTuner to finetune with it. SimpleTuner has extensive support for parameter-efficient fine-tuning via [LyCORIS](https://github.com/KohakuBlueleaf/LyCORIS), in addition to full-rank fine-tuning. For inference, use the custom pipline from this repo and [follow the example in SimpleTuner to patch in your LyCORIS weights](https://github.com/bghira/SimpleTuner/blob/main/documentation/LYCORIS.md).
 
+```py
+from lycoris import create_lycoris_from_weights
+
+pipe = DiffusionPipeline.from_pretrained(
+    "jimmycarter/LibreFLUX",
+    custom_pipeline="jimmycarter/LibreFLUX",
+    use_safetensors=True,
+    torch_dtype=torch.bfloat16,
+    trust_remote_code=True,
+)
+
+lycoris_safetensors_path = 'pytorch_lora_weights.safetensors'
+wrapper, _ = create_lycoris_from_weights(1.0, lycoris_safetensors_path, pipe.transformer)
+wrapper.merge_to()
+del wrapper
+
+prompt = "Photograph of a chalk board on which is written: 'I thought what I'd do was, I'd pretend I was one of those deaf-mutes.'"
+negative_prompt = "blurry"
+images = pipe(
+  prompt=prompt,
+  negative_prompt=negative_prompt,
+  return_dict=False,
+)
+images[0][0].save('chalkboard.png')
+
+# optionally, save a merged pipeline containing the LyCORIS baked-in:
+# pipe.save_pretrained('/path/to/output/pipeline')
+```
+
 # Non-technical Report on Schnell De-distillation
 
 Welcome to my non-technical report on de-distilling FLUX.1-schnell in the most un-scientific way possible with extremely limited resources. I'm not going to claim I made a good model, but I did make a model. It was trained on about 1,500 H100 hour equivalents.