Instructions to use puliatti/fill_hyper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use puliatti/fill_hyper with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("puliatti/fill_hyper", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Diffusion Single File
How to use puliatti/fill_hyper with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Alex Puliatti commited on
Delete transformer/config.json
Browse files- transformer/config.json +0 -19
transformer/config.json
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{
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"_class_name": "FluxTransformer2DModel",
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"_diffusers_version": "0.32.0.dev0",
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"attention_head_dim": 128,
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"axes_dims_rope": [
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16,
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56,
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56
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],
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"guidance_embeds": true,
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"in_channels": 384,
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"joint_attention_dim": 4096,
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"num_attention_heads": 24,
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"num_layers": 19,
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"num_single_layers": 38,
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"out_channels": 64,
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"patch_size": 1,
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"pooled_projection_dim": 768
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}
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