Instructions to use ChengYangYang/bpp-reading-pointer-weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ChengYangYang/bpp-reading-pointer-weights with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ChengYangYang/bpp-reading-pointer-weights", 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 files
reader_weights/INDEX.json
CHANGED
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@@ -463,7 +463,7 @@
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},
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{
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"run": "2026.09.30/06.05.45_combLEVT2_s0_policy_liberogen_spatial_combination_prompt_diffusion_unet",
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"ckpt": "/data/jgu/cheng/bpp_repo/behavior_prompting/train_network/runs/2026.09.30/06.05.45_combLEVT2_s0_policy_liberogen_spatial_combination_prompt_diffusion_unet/checkpoints/
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"n_reader_tensors": 12,
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"n_reader_params": 400561,
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"policy_trained": false
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},
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{
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"run": "2026.09.30/06.05.45_combLEVT2_s0_policy_liberogen_spatial_combination_prompt_diffusion_unet",
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"ckpt": "/data/jgu/cheng/bpp_repo/behavior_prompting/train_network/runs/2026.09.30/06.05.45_combLEVT2_s0_policy_liberogen_spatial_combination_prompt_diffusion_unet/checkpoints/step_003000.ckpt",
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"n_reader_tensors": 12,
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"n_reader_params": 400561,
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"policy_trained": false
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