End of training

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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+image_0.png filter=lfs diff=lfs merge=lfs -text
+image_1.png filter=lfs diff=lfs merge=lfs -text
+image_2.png filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+tags:
+- stable-diffusion-xl
+- stable-diffusion-xl-diffusers
+- text-to-image
+- diffusers
+- lora
+- template:sd-lora
+widget:
+
+        - text: '<s0><s1> webpage about the movie Mean Girls'
+          output:
+            url:
+                "image_0.png"
+        
+        - text: '<s0><s1> webpage about the movie Mean Girls'
+          output:
+            url:
+                "image_1.png"
+        
+        - text: '<s0><s1> webpage about the movie Mean Girls'
+          output:
+            url:
+                "image_2.png"
+        
+        - text: '<s0><s1> webpage about the movie Mean Girls'
+          output:
+            url:
+                "image_3.png"
+        
+base_model: stabilityai/stable-diffusion-xl-base-1.0
+instance_prompt: a webpage in the style of <s0><s1>
+license: openrail++
+---
+
+# SDXL LoRA DreamBooth - LinoyTsaban/web_y2k_v6
+
+<Gallery />
+
+## Model description
+
+### These are LinoyTsaban/web_y2k_v6 LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
+
+## Trigger words
+
+To trigger image generation of trained concept(or concepts) replace each concept identifier in you prompt with the new inserted tokens:
+
+to trigger concept `TOK` → use `<s0><s1>` in your prompt 
+
+
+
+## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
+
+```py
+from diffusers import AutoPipelineForText2Image
+import torch
+from huggingface_hub import hf_hub_download
+from safetensors.torch import load_file
+        
+pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
+pipeline.load_lora_weights('LinoyTsaban/web_y2k_v6', weight_name='pytorch_lora_weights.safetensors')
+embedding_path = hf_hub_download(repo_id='LinoyTsaban/web_y2k_v6', filename="embeddings.safetensors", repo_type="model")
+state_dict = load_file(embedding_path)
+pipeline.load_textual_inversion(state_dict["clip_l"], token=["<s0>", "<s1>"], text_encoder=pipe.text_encoder, tokenizer=pipe.tokenizer)
+pipeline.load_textual_inversion(state_dict["clip_g"], token=["<s0>", "<s1>"], text_encoder=pipe.text_encoder_2, tokenizer=pipe.tokenizer_2)
+        
+image = pipeline('<s0><s1> webpage about the movie Mean Girls').images[0]
+```
+
+For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
+
+## Download model
+
+### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
+
+- Download the LoRA *.safetensors [here](/LinoyTsaban/web_y2k_v6/blob/main/pytorch_lora_weights.safetensors). Rename it and place it on your Lora folder.
+- Download the text embeddings *.safetensors [here](/LinoyTsaban/web_y2k_v6/blob/main/embeddings.safetensors). Rename it and place it on it on your embeddings folder.
+
+All [Files & versions](/LinoyTsaban/web_y2k_v6/tree/main).
+
+## Details
+
+The weights were trained using [🧨 diffusers Advanced Dreambooth Training Script](https://github.com/huggingface/diffusers/blob/main/examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py).
+
+LoRA for the text encoder was enabled. False.
+
+Pivotal tuning was enabled: True.
+
+Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
+

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