Instructions to use ahishamm/vit-large-binary-isic-patch-16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahishamm/vit-large-binary-isic-patch-16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahishamm/vit-large-binary-isic-patch-16") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ahishamm/vit-large-binary-isic-patch-16") model = AutoModelForImageClassification.from_pretrained("ahishamm/vit-large-binary-isic-patch-16") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 4000
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1213348653
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2cfae9858e993e38e96c39e95ea05507929df400247c51adc6869685f4ae5ca5
|
| 3 |
size 1213348653
|
runs/Jul01_14-22-11_9e49da66a448/events.out.tfevents.1688221337.9e49da66a448.1494.4
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:f79e58aeae46f340e620bda0643562949ce2745e7759e7fcf7ed479fdf02382b
|
| 3 |
+
size 85693
|