Instructions to use dexforint/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dexforint/checkpoints with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("dexforint/checkpoints") model = SegformerForSemanticSegmentation.from_pretrained("dexforint/checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 7500
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 256307093
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4da926c1325d3ee48b81d97444d2e0471004c52d18b7b504fd49656eba7c7063
|
| 3 |
size 256307093
|
runs/Jun12_21-30-22_a609e0900d96/events.out.tfevents.1686605499.a609e0900d96.23.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:27e33c66d711f692c66652c10b7004ff4826ac0383b59bfa3f3f0d420b25b79a
|
| 3 |
+
size 28057
|