Instructions to use YuCollection/sdxl-1.0-refiner-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YuCollection/sdxl-1.0-refiner-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YuCollection/sdxl-1.0-refiner-diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Upload text_encoder_2/config.json with huggingface_hub
Browse files- text_encoder_2/config.json +24 -0
text_encoder_2/config.json
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{
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"architectures": [
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"CLIPTextModelWithProjection"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 0,
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"dropout": 0.0,
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"eos_token_id": 2,
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"hidden_act": "gelu",
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"hidden_size": 1280,
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"initializer_factor": 1.0,
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"initializer_range": 0.02,
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"intermediate_size": 5120,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 77,
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"model_type": "clip_text_model",
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"num_attention_heads": 20,
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"num_hidden_layers": 32,
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"pad_token_id": 1,
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"projection_dim": 1280,
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"torch_dtype": "float16",
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"transformers_version": "4.32.0.dev0",
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"vocab_size": 49408
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}
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