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mlboydaisuke
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coreml-zoo

Core ML
core-ml
ios
macos
apple
on-device
model-zoo
coremltools
mlpackage
arxiv:1808.00897
arxiv:2009.09960
arxiv:2101.04061
arxiv:2107.10833
arxiv:2109.07161
arxiv:2204.00964
arxiv:2211.08553
arxiv:2212.11613
arxiv:2303.14535
arxiv:2303.15343
arxiv:2306.07691
arxiv:2306.14289
arxiv:2310.13025
arxiv:2311.06242
arxiv:2311.14760
arxiv:2312.01479
arxiv:2401.17270
arxiv:2404.13686
arxiv:2405.14458
arxiv:2501.14677
arxiv:2503.07465
arxiv:2505.08175
arxiv:2507.02546
arxiv:2511.09554
arxiv:2511.10647
Model card Files
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 Community
coreml-zoo

Commit History

  1. Link the card back to its collection and the request box

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  1. Add README.md

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  2. Correct three licenses: RMBG-1.4, SinSR and MatAnyone are non-commercial

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  3. Add README.md

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  4. Add README.md

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  1. Revert: pull YOLOE from live manifest (pending app 3.0)

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  2. Add YOLOE (open-vocab detection + segmentation)

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  3. Add yoloe/mobileclip_blt_text.mlpackage.zip

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  4. Add yoloe/reprta_s.mlpackage.zip

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  5. Add yoloe/yoloe_detector_s.mlpackage.zip

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  1. Bump CoreML-LLM references to v1.4 (3-chunk decode, chunk pipelining)

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  2. Add Gemma 4 E4B, Qwen3.5 2B/0.8B, Qwen3-VL 2B (CoreML-LLM v1.3); refresh Gemma 4 E2B (audio/video, 3.1 GB)

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  1. Upload models.json with huggingface_hub

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  2. Upload pixelization/Pixelization_512.mlpackage.zip with huggingface_hub

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  1. nitroe: switch template to text_to_image_nitroe

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  2. Add Nitro-E (AMD 304M E-MMDiT, 4-step) to manifest

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  3. nitroe: swap E-MMDiT to INT8 palettized (578MB -> 295MB)

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  4. nitroe: Llama3Merges.txt

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  5. nitroe: Llama3Vocab.json

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  6. nitroe: NitroE_VAEDecoder.mlpackage.zip

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  7. nitroe: NitroE_EMMDiT.mlpackage.zip

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  8. nitroe: NitroE_TextEncoder.mlpackage.zip

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  1. Add Depth Anything 3 Small/Base entries

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  2. Add DepthAnythingV3_base_504.mlpackage.zip

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  3. Add DepthAnythingV3_small_504.mlpackage.zip

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  1. Add conversion_script_url to 13 models⁠

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  2. Optimize compute_units: Kokoro decoders, HyperSD text encoder, StableAudio T5/NumberEmbedder

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  1. Upload models.json with huggingface_hub

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  2. Upload gfpgan/GFPGAN.mlpackage.zip with huggingface_hub

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  3. Upload realesrgan/RealESRGAN_x4.mlpackage.zip with huggingface_hub

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  4. Upload faceparsing/FaceParsing.mlpackage.zip with huggingface_hub

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  5. Upload models.json with huggingface_hub

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  6. Upload gfpgan/GFPGAN.mlpackage.zip with huggingface_hub

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  7. Upload realesrgan/RealESRGAN_x4.mlpackage.zip with huggingface_hub

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  8. Upload models.json with huggingface_hub

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  9. Upload faceparsing/FaceParsing.mlpackage.zip with huggingface_hub

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  10. Upload models.json with huggingface_hub

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  11. Upload efficientad/EfficientAD_Bottle.mlpackage.zip with huggingface_hub

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  12. Upload adaface/AdaFace_IR18.mlpackage.zip with huggingface_hub

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  13. Upload models.json with huggingface_hub

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  14. Upload models.json with huggingface_hub

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  15. Upload lama/LaMa.mlpackage.zip with huggingface_hub

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  16. Upload gfpgan/GFPGAN.mlpackage.zip with huggingface_hub

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  17. Upload rfdetr/rfdetr_n_coco.mlpackage.zip with huggingface_hub

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  18. Upload mobilesam/MobileSAM.zip with huggingface_hub

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  19. Upload faceparsing/FaceParsing.mlpackage.zip with huggingface_hub

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  20. Upload realesrgan/RealESRGAN_x4.mlpackage.zip with huggingface_hub

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  1. Upload models.json with huggingface_hub

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  2. Upload models.json with huggingface_hub

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  3. Upload models.json with huggingface_hub

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