Instructions to use YiYiXu/shap-e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YiYiXu/shap-e with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("YiYiXu/shap-e", 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
- Local Apps
- Draw Things
- DiffusionBee
yiyixuxu commited on
Commit ·
eacca6e
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Parent(s): adc6ebc
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prior/diffusion_pytorch_model.fp16.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:04ad95e7374796a817f5b5a32b885be457b013ffdadf5da2f99883886f417aac
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size 631435880
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renderer/config.json
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"_class_name": "ShapERenderer",
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"_diffusers_version": "0.18.0.dev0",
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"act_fn": "swish",
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"d_hidden": 256,
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"d_latent": 1024,
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"insert_direction_at": 4,
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"_class_name": "ShapERenderer",
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"_diffusers_version": "0.18.0.dev0",
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"act_fn": "swish",
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"background": [
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255.0,
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255.0,
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255.0
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],
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"d_hidden": 256,
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"d_latent": 1024,
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"insert_direction_at": 4,
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renderer/diffusion_pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:134b0ea32cf69fdb86f4303b6b1910fb5c391e7158a0dd89c91dbe037ebcc67c
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size 905233202
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renderer/diffusion_pytorch_model.fp16.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:394d52e159447b2bfb944d3bfa4f438180b72ba40644dc4c730282e7a9b62c65
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size 452597858
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scheduler/scheduler_config.json
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"clip_sample": true,
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"clip_sample_range": 1.0,
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"prediction_type": "sample",
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"use_karras_sigmas": true
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}
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"clip_sample": true,
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"clip_sample_range": 1.0,
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"prediction_type": "sample",
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"use_karras_sigmas": true
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}
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