Instructions to use simlaharma/vit-base-cifar10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simlaharma/vit-base-cifar10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="simlaharma/vit-base-cifar10") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("simlaharma/vit-base-cifar10") model = AutoModelForImageClassification.from_pretrained("simlaharma/vit-base-cifar10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
8730e0e
1
Parent(s): 6d0c215
Training in progress, epoch 2
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 343293293
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a8aec5897c78e841f94bec7b1b6bb7c3f47df79444f229b3f9af1b9e83b10e8d
|
| 3 |
size 343293293
|