Instructions to use varcoder/CrackSeg-MIT-b0-dice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varcoder/CrackSeg-MIT-b0-dice with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("varcoder/CrackSeg-MIT-b0-dice") model = SegformerForSemanticSegmentation.from_pretrained("varcoder/CrackSeg-MIT-b0-dice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 3800
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 109529789
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:88a65e52ad65c6470c0d6e27d4f908c6101a554899ade9ca9eddcd001abcb36e
|
| 3 |
size 109529789
|