Instructions to use kp-forks/InstantMesh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kp-forks/InstantMesh with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kp-forks/InstantMesh", 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
Browse files- diffusion_pytorch_model.bin +3 -0
- instant_mesh_base.ckpt +3 -0
- instant_mesh_large.ckpt +3 -0
- instant_nerf_base.ckpt +3 -0
- instant_nerf_large.ckpt +3 -0
diffusion_pytorch_model.bin
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oid sha256:9d78d78421d1feb6871d13e13e86ed8099628648d7d9c51ffca9015b7d5fa3c4
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instant_mesh_base.ckpt
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oid sha256:22701cd25201d624ebb1568b93cf91b43a2c32006835c08fe73e1f3c9f6c44b5
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size 1253574354
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instant_mesh_large.ckpt
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oid sha256:329f7aae9b583fd7c1b27d0221463db7b808a03c48a1f7aa26649af6a03b91a1
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size 1514818077
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instant_nerf_base.ckpt
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oid sha256:bcbfff8be8545f8206110f432afddedfb4311abc1146b843ab2bdb6678f8d9c9
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size 1253151890
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instant_nerf_large.ckpt
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oid sha256:530a344ea9b856e012492b9644ab73532ddf7c06d548f60c489e49a528322fb9
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size 1514088389
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