Image Segmentation
MLX
apple-silicon
video-matting
green-screen
blue-screen
chroma-key
vfx
fp32
fp16
quantized
Instructions to use cdelta/CorridorKey-v2-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use cdelta/CorridorKey-v2-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download cdelta/CorridorKey-v2-MLX --local-dir CorridorKey-v2-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download weight-verification.json from cdelta/CorridorKey-v2-MLX: direct link, hf CLI and curl.
- Browser
- Download file 585 Bytes
-
https://huggingface.co/cdelta/CorridorKey-v2-MLX/resolve/main/weight-verification.json
- Command line
-
hf download hf://cdelta/CorridorKey-v2-MLX/weight-verification.json
-
curl -L -o weight-verification.json https://huggingface.co/cdelta/CorridorKey-v2-MLX/resolve/main/weight-verification.json
585 Bytes
| { | |
| "upstream": "nikopueringer/CorridorKey2.0", | |
| "revision": "cf44a8db3f024bb49fd59daa408848ccf05f7477", | |
| "tensor_count": 738, | |
| "missing_or_extra": [], | |
| "unequal_tensors": [], | |
| "model_config_equal": true, | |
| "public_safetensors_sha256": "c43596de98cc8866d577c8a9f9ea239acdf3f7a130ff24e25db4375a50590436", | |
| "stats_keys": [ | |
| "cradio_mean", | |
| "cradio_std", | |
| "moge_mean", | |
| "moge_std", | |
| "rvm_mean", | |
| "rvm_std" | |
| ], | |
| "stats_equal": true, | |
| "passed": true, | |
| "method": "SHA-256 of conversion-input and official-release tensor bytes, with exact shape/dtype agreement" | |
| } | |