Instructions to use piddnad/ddcolor_modelscope with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use piddnad/ddcolor_modelscope with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("piddnad/ddcolor_modelscope", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from piddnad/ddcolor_modelscope: direct link, hf CLI and curl.
- Browser
- Download file 258 Bytes
-
https://huggingface.co/piddnad/ddcolor_modelscope/resolve/main/config.json
- Command line
-
hf download hf://piddnad/ddcolor_modelscope/config.json
-
curl -L -o config.json https://huggingface.co/piddnad/ddcolor_modelscope/resolve/main/config.json
258 Bytes
| { | |
| "encoder_name": "convnext-l", | |
| "decoder_name": "MultiScaleColorDecoder", | |
| "input_size": [ | |
| 512, | |
| 512 | |
| ], | |
| "num_output_channels": 2, | |
| "last_norm": "Spectral", | |
| "do_normalize": false, | |
| "num_queries": 100, | |
| "num_scales": 3, | |
| "dec_layers": 9 | |
| } |