Instructions to use masafresh/vit-transformer3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use masafresh/vit-transformer3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="masafresh/vit-transformer3") 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("masafresh/vit-transformer3") model = AutoModelForImageClassification.from_pretrained("masafresh/vit-transformer3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 76
Browse files
logs/events.out.tfevents.1731833820.AZHAR-PC.48135.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:cf761e20e9df855b20416466423ea38897731bdbf0077acc65f46fbfcb4e92a4
|
| 3 |
+
size 60035
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1213289972
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5e40f23a0fd4e2efbbf5a0c458f09a758025fd5c7a7dfb5750e8e501c15cbbc3
|
| 3 |
size 1213289972
|