End of training
Browse files- README.md +95 -0
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- living-room-sd-1-5-32_100.safetensors +3 -0
- living-room-sd-1-5-32_100_emb.safetensors +3 -0
- pytorch_lora_weights.safetensors +3 -0
README.md
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---
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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- diffusers-training
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- text-to-image
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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: 'living room - kitchen in the style of <s0><s1> with a open floor plan, featuring a coffee table, a couch, a chandelier, and a set of dining table'
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output:
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url:
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"image_0.png"
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- text: 'living room - kitchen in the style of <s0><s1> with a open floor plan, featuring a coffee table, a couch, a chandelier, and a set of dining table'
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output:
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url:
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"image_1.png"
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- text: 'living room - kitchen in the style of <s0><s1> with a open floor plan, featuring a coffee table, a couch, a chandelier, and a set of dining table'
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output:
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url:
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"image_2.png"
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- text: 'living room - kitchen in the style of <s0><s1> with a open floor plan, featuring a coffee table, a couch, a chandelier, and a set of dining table'
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output:
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url:
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"image_3.png"
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base_model: runwayml/stable-diffusion-v1-5
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instance_prompt: living room - kitchen in style of <s0><s1> with an open floor plan
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license: openrail++
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---
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# SD1.5 LoRA DreamBooth - htuannn/living-room-sd-1-5-32_100
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<Gallery />
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## Model description
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### These are htuannn/living-room-sd-1-5-32_100 LoRA adaption weights for runwayml/stable-diffusion-v1-5.
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## Download model
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### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
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- **LoRA**: download **[`living-room-sd-1-5-32_100.safetensors` here 💾](/htuannn/living-room-sd-1-5-32_100/blob/main/living-room-sd-1-5-32_100.safetensors)**.
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- Place it on your `models/Lora` folder.
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- On AUTOMATIC1111, load the LoRA by adding `<lora:living-room-sd-1-5-32_100:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
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- *Embeddings*: download **[`living-room-sd-1-5-32_100_emb.safetensors` here 💾](/htuannn/living-room-sd-1-5-32_100/blob/main/living-room-sd-1-5-32_100_emb.safetensors)**.
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- Place it on it on your `embeddings` folder
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- Use it by adding `living-room-sd-1-5-32_100_emb` to your prompt. For example, `living room - kitchen in style of living-room-sd-1-5-32_100_emb with an open floor plan`
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(you need both the LoRA and the embeddings as they were trained together for this 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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from huggingface_hub import hf_hub_download
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from safetensors.torch import load_file
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pipeline = AutoPipelineForText2Image.from_pretrained('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to('cuda')
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pipeline.load_lora_weights('htuannn/living-room-sd-1-5-32_100', weight_name='pytorch_lora_weights.safetensors')
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embedding_path = hf_hub_download(repo_id='htuannn/living-room-sd-1-5-32_100', filename='living-room-sd-1-5-32_100_emb.safetensors', repo_type="model")
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state_dict = load_file(embedding_path)
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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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image = pipeline('living room - kitchen in the style of <s0><s1> with a open floor plan, featuring a coffee table, a couch, a chandelier, and a set of dining table').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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To trigger image generation of trained concept(or concepts) replace each concept identifier in you prompt with the new inserted tokens:
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to trigger concept `TOK` → use `<s0><s1>` in your prompt
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## Details
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All [Files & versions](/htuannn/living-room-sd-1-5-32_100/tree/main).
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The weights were trained using [🧨 diffusers Advanced Dreambooth Training Script](https://github.com/huggingface/diffusers/blob/main/examples/advanced_diffusion_training/train_dreambooth_lora_sd15_advanced.py).
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LoRA for the text encoder was enabled. False.
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Pivotal tuning was enabled: True.
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Special VAE used for training: None.
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image_0.png
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image_1.png
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image_2.png
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image_3.png
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living-room-sd-1-5-32_100.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:72d19cc66a728b920c63b5a4e5c1fbf14d578471670172beea29d40cd3b4c19e
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size 25986232
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living-room-sd-1-5-32_100_emb.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5b6396b63b21770c9d1459a47133078d8c0a7b7fe3d0518ef624cd3ce4666eb9
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size 3152
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pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:07a2f7b9d5d2ad5357de98147586e27d47797f1015c3384fc3fa4a7f3d47f6c9
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size 25966896
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