End of training
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- pytorch_lora_weights.safetensors +1 -1
.gitattributes
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README.md
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---
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tags:
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- stable-diffusion-xl
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- stable-diffusion-xl-diffusers
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- diffusers
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- dora
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- template:sd-lora
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widget:
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output:
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url:
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output:
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url:
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base_model: stabilityai/stable-diffusion-xl-base-1.0
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instance_prompt: a
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license: openrail++
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---
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- **LoRA**: download **[`huggy_dora_v2.safetensors` here 💾](/linoyts/huggy_dora_v2/blob/main/huggy_dora_v2.safetensors)**.
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- Place it on your `models/Lora` folder.
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- On AUTOMATIC1111, load the LoRA by adding `<lora:huggy_dora_v2:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
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-
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- Place it on it on your `embeddings` folder
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- Use it by adding `huggy_dora_v2_emb` to your prompt. For example, `a huggy_dora_v2_emb emoji`
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(you need both the LoRA and the embeddings as they were trained together for this LoRA)
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-
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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```py
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from diffusers import AutoPipelineForText2Image
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import torch
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-
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from safetensors.torch import load_file
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pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
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pipeline.load_lora_weights('linoyts/huggy_dora_v2', weight_name='pytorch_lora_weights.safetensors')
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-
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-
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pipeline.load_textual_inversion(state_dict["clip_l"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
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pipeline.load_textual_inversion(state_dict["clip_g"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
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-
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image = pipeline('a <s0><s1> emoji dressed as yoda').images[0]
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```
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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)
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## Trigger words
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-
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-
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to trigger concept `TOK` → use `<s0><s1>` in your prompt
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-
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-
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## Details
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All [Files & versions](/linoyts/huggy_dora_v2/tree/main).
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LoRA for the text encoder was enabled. False.
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Pivotal tuning was enabled:
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Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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---
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+
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tags:
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- stable-diffusion-xl
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- stable-diffusion-xl-diffusers
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- diffusers
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- dora
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- template:sd-lora
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widget:
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- text: 'a TOK emoji dressed as an easter bunny'
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output:
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url:
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"image_0.png"
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- text: 'a TOK emoji dressed as an easter bunny'
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output:
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url:
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"image_1.png"
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- text: 'a TOK emoji dressed as an easter bunny'
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output:
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url:
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"image_2.png"
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- text: 'a TOK emoji dressed as an easter bunny'
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output:
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url:
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"image_3.png"
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base_model: stabilityai/stable-diffusion-xl-base-1.0
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instance_prompt: a TOK emoji
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license: openrail++
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---
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- **LoRA**: download **[`huggy_dora_v2.safetensors` here 💾](/linoyts/huggy_dora_v2/blob/main/huggy_dora_v2.safetensors)**.
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- Place it on your `models/Lora` folder.
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- On AUTOMATIC1111, load the LoRA by adding `<lora:huggy_dora_v2:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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```py
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from diffusers import AutoPipelineForText2Image
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import torch
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pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
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pipeline.load_lora_weights('linoyts/huggy_dora_v2', weight_name='pytorch_lora_weights.safetensors')
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image = pipeline('a TOK emoji dressed as an easter bunny').images[0]
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```
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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)
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## Trigger words
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You should use a TOK emoji to trigger the image generation.
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## Details
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All [Files & versions](/linoyts/huggy_dora_v2/tree/main).
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LoRA for the text encoder was enabled. False.
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Pivotal tuning was enabled: False.
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Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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