Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use dingusagar/vit-base-avengers-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dingusagar/vit-base-avengers-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dingusagar/vit-base-avengers-v1") 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("dingusagar/vit-base-avengers-v1") model = AutoModelForImageClassification.from_pretrained("dingusagar/vit-base-avengers-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
2eb9b0d
1
Parent(s): 88ed233
Model save
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 343310001
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:11a057b518870c88151ed204cd7cf53aec95db6d29cc51393b52aea7b70202ca
|
| 3 |
size 343310001
|
runs/Jul10_06-36-03_bb12060d810a/events.out.tfevents.1657434967.bb12060d810a.73.2
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:e20104724f1655089e64c47d3d4318ac2e4dff130e0797c2161f07a10efdb3ec
|
| 3 |
+
size 10463
|