Instructions to use p1atdev/MangaLineExtraction-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use p1atdev/MangaLineExtraction-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-to-image", model="p1atdev/MangaLineExtraction-hf", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("p1atdev/MangaLineExtraction-hf", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "MLEForAnimeLineExtraction" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_mle.MLEConfig", | |
| "AutoModel": "modeling_mle.MLEForAnimeLineExtraction" | |
| }, | |
| "batch_norm_eps": 0.001, | |
| "block_kernel_size": 3, | |
| "block_patch_size": 24, | |
| "block_stride_size": 4, | |
| "hidden_act": "leaky_relu", | |
| "in_channels": 1, | |
| "last_hidden_channels": 16, | |
| "model_type": "mle", | |
| "negative_slope": 0.2, | |
| "num_decoder_layers": [ | |
| 7, | |
| 5, | |
| 3, | |
| 2, | |
| 2 | |
| ], | |
| "num_encoder_layers": [ | |
| 2, | |
| 3, | |
| 5, | |
| 7, | |
| 12 | |
| ], | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.37.2", | |
| "upsample_ratio": 2 | |
| } | |