Instructions to use Claquasse/Anima-Control-Pose with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Claquasse/Anima-Control-Pose with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Claquasse/Anima-Control-Pose", 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 Settings
- Draw Things
- DiffusionBee
Commit History
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Pose node: HF->mirror detector fetch with size guard (China-friendlier), keeps openmmlab fallback
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Pose node clears stale/corrupt rtmlib .zip partials (fixes BadZipFile from failed openmmlab downloads)
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Pose node auto-fetches rtmlib detector from HF (detector/) instead of openmmlab; README note + rebuilt tools zip
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Add rtmlib detector ONNX models (yolox + rtmw-dw-x-l) so the pose node can fetch from HF instead of openmmlab
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fix: bundle control_embedder.py + relative import in anima_control_lora node (fixes ModuleNotFoundError: anima_control)
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Preview-2: multi-resolution pose adapter (512/768/1024) + Anima Pose Control node + workflows
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Enable download tracking (library_name: diffusers counts top-level safetensors)
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Anima Control — Pose (Preview-1): adapter, node, workflows, samples, card
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initial commit
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