Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Dhika/leaves with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dhika/leaves with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Dhika/leaves") 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/leaves") model = AutoModelForImageClassification.from_pretrained("Dhika/leaves", 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 343265965
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ed6881f89a22658a140e0b77d5dc7e0b3cb7ebdd00244d125d42215848d4a9fe
|
| 3 |
size 343265965
|
runs/May24_14-33-43_ddd353ae11b5/events.out.tfevents.1684938844.ddd353ae11b5.383.0
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 sha256:9767aa1593c61d4edc8154d8ec5668d8fc2df6b58fe3e64f69b762e0ac13ce74
|
| 3 |
+
size 6801
|