Instructions to use abhinavkk/cifar10_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abhinavkk/cifar10_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="abhinavkk/cifar10_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("abhinavkk/cifar10_model") model = AutoModelForImageClassification.from_pretrained("abhinavkk/cifar10_model") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 0
Browse files- pytorch_model.bin +1 -1
- training_args.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 sha256:64b078d066f0162ed4d018748c405851351be5470ac845b9b24522022666e9bf
|
| 3 |
size 343293293
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 3387
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:206e9ee037990e8a86659ce60d4eeaeafcbc98361c013874f1695ac619faabfe
|
| 3 |
size 3387
|