Instructions to use theoberva/UBCO-Model-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use theoberva/UBCO-Model-512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="theoberva/UBCO-Model-512") 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("theoberva/UBCO-Model-512") model = AutoModelForImageClassification.from_pretrained("theoberva/UBCO-Model-512") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 41
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 347764401
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6227cdfc58785e347a211f4ba753611cf768279d1791b36ca37f26f846d002f6
|
| 3 |
size 347764401
|