Instructions to use RobertML/edge-super-compile-08 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RobertML/edge-super-compile-08 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RobertML/edge-super-compile-08", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Add files using upload-large-folder tool
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
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onnx/up_blocks.0/attentions.1.transformer_blocks.8.norm3.weight
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onnx/up_blocks.0/attentions.1.transformer_blocks.9.attn2.to_out.0.bias
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Binary file (2.56 kB). View file
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onnx/up_blocks.0/attentions.1.transformer_blocks.9.ff.net.0.proj.bias
ADDED
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onnx/up_blocks.0/attentions.1.transformer_blocks.9.norm1.weight
ADDED
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Binary file (2.56 kB). View file
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onnx/up_blocks.0/attentions.1.transformer_blocks.9.norm2.bias
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Binary file (2.56 kB). View file
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onnx/up_blocks.0/attentions.2.transformer_blocks.0.attn1.to_out.0.bias
ADDED
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Binary file (2.56 kB). View file
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onnx/up_blocks.0/attentions.2.transformer_blocks.0.norm3.weight
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Binary file (2.56 kB). View file
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onnx/up_blocks.0/attentions.2.transformer_blocks.1.ff.net.2.bias
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