Instructions to use molsen/beitv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use molsen/beitv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="molsen/beitv2") 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("molsen/beitv2") model = AutoModelForImageClassification.from_pretrained("molsen/beitv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 22
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 346857337
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e704eed872a7af2902e46ec4c793b5ad80d49ba8126b158008e8130620465d45
|
| 3 |
size 346857337
|