Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Dhika/raildefectfft1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dhika/raildefectfft1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Dhika/raildefectfft1") 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("Dhika/raildefectfft1") model = AutoModelForImageClassification.from_pretrained("Dhika/raildefectfft1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 60
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 343278253
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b4baa7dffc7b1cd7c081464ae1e06ee13a5b1f99f7ac89e26532725b7019d325
|
| 3 |
size 343278253
|
runs/Jun11_10-18-16_46819e1563a4/events.out.tfevents.1686478710.46819e1563a4.17989.0
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:ce1a513df8e9feef873ce94e7af374b2d74e95ecc12a3cc9440ed50ecc7a82d4
|
| 3 |
+
size 6987
|