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--- |
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license: openrail++ |
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library_name: diffusers |
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tags: |
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- text-to-image |
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- diffusers-training |
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- diffusers |
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- lora |
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- template:sd-lora |
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- stable-diffusion-xl |
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- stable-diffusion-xl-diffusers |
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base_model: stabilityai/stable-diffusion-xl-base-1.0 |
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instance_prompt: a photo of TOK dog |
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widget: |
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- text: Draw a picture of two female boxers fighting each other. |
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output: |
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url: images/example_9xsyd09gw.png |
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datasets: |
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- ZB-Tech/DreamXL |
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language: |
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- en |
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--- |
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<!-- This model card has been generated automatically according to the information the training script had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# SDXL LoRA Fine-tuning - ZB-Tech/Text-To-Image |
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<Gallery /> |
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## Model description |
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These are ZB-Tech/Text-to-Image LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. |
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LoRA for the text encoder was enabled: False. |
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Special VAE used for training: madebyollin/sdxl-vae-fp16-fix. |
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##### How to use |
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```python |
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import requests |
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API_URL = "https://api-inference.huggingface.co/models/ZB-Tech/Text-to-Image" |
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headers = {"Authorization": "Bearer HF_API_KEY"} |
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def query(payload): |
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response = requests.post(API_URL, headers=headers, json=payload) |
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return response.content |
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image_bytes = query({ |
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"inputs": "Astronaut riding a horse", |
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}) |
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# You can access the image with PIL.Image for example |
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import io |
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from PIL import Image |
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image = Image.open(io.BytesIO(image_bytes)) |
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``` |
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## Download model |
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Weights for this model are available in Safetensors format. |
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[Download](suryasuri/Surya/tree/main) them in the Files & versions tab. |
