Instructions to use ahishamm/vit-large-binary-isic-sharpened-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-sharpened-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-sharpened-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-sharpened-patch-16") model = AutoModelForImageClassification.from_pretrained("ahishamm/vit-large-binary-isic-sharpened-patch-16") - Notebooks
- Google Colab
- Kaggle
Model save
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 sha256:2da5da5ad43468fb0f116e4f39885a23ac53d6d09608d6ca7c1684e38c2e6642
|
| 3 |
size 1213348653
|
runs/Jul01_14-36-24_293c456ba153/events.out.tfevents.1688222189.293c456ba153.1472.4
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 sha256:3d5ae2b21a9cab99e5555803b6be031e44605ac46c96e8e8e986fa7cbe1462ce
|
| 3 |
+
size 92517
|