Instructions to use jiuntian/OneHOI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jiuntian/OneHOI with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jiuntian/OneHOI", 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
Upload folder using huggingface_hub
Browse files
grounding_encoder.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5429248b1845580f9614cb12e8e69dc2172c7e7f6632efa2251c0064c03a5f15
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size 34896770
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grounding_encoder/config.json
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{
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"_class_name": "GroundingEncoder",
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"_diffusers_version": "0.35.0.dev0",
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"fourier_freq": 32,
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"hidden_size": 2048,
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"init_logit": -5.0,
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"max_hoi_seq": 32,
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"mlp_out_std": 0.0003,
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"n_roles": 3,
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"pos_embed_dim": 32,
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"role_embed_dim": 32,
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"role_std": 0.02,
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"text_encoder_dim": 4096
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}
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pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:15c0e0c2da2bd8a4a6e59fd45d041a3395698238e84082f2f537eb5ba6a7b3f0
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size 687880408
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