Instructions to use recoilme/transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use recoilme/transformer with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("recoilme/transformer", 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
Upload folder using huggingface_hub
Browse files- config.json +1 -1
- diffusion_pytorch_model.safetensors +1 -1
config.json
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{
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"_class_name": "CosmosTransformer3DModel",
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"_diffusers_version": "0.
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"_name_or_path": "transformer",
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"adaln_lora_dim": 256,
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"attention_head_dim": 128,
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{
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"_class_name": "CosmosTransformer3DModel",
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"_diffusers_version": "0.37.1",
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"_name_or_path": "transformer",
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"adaln_lora_dim": 256,
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"attention_head_dim": 128,
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diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 7825687184
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