Text-to-Image
Diffusers
TensorBoard
Safetensors
English
StableDiffusionPipeline
diffusers-training
lora
template:sd-lora
stable-diffusion-xl
stable-diffusion-xl-diffusers
Instructions to use ZB-Tech/Text-to-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ZB-Tech/Text-to-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ZB-Tech/Text-to-Image") prompt = "Draw a picture of two female boxers fighting each other." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update README.md
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README.md
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library_name: diffusers
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tags:
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- text-to-image
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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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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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---
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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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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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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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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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