Instructions to use randomstate42/vit_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use randomstate42/vit_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="randomstate42/vit_model") 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("randomstate42/vit_model") model = AutoModelForImageClassification.from_pretrained("randomstate42/vit_model") - Notebooks
- Google Colab
- Kaggle
Commit ·
6f1b502
1
Parent(s): 4f9c8ca
Training in progress, epoch 6
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 343508653
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:35fd1e5a4eafde20f976f3116cbbb55d2a0acf52740ecb82ef50f7cce75e6d5d
|
| 3 |
size 343508653
|