Instructions to use jayanta/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayanta/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jayanta/test") 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("jayanta/test") model = AutoModelForImageClassification.from_pretrained("jayanta/test") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 52
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 94374989
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e10f43fa5f8f5034445809f22833746509187164bb26517ca0db6af670b38532
|
| 3 |
size 94374989
|
runs/Jul08_15-52-47_teesta/events.out.tfevents.1688811778.teesta.27493.0
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 sha256:6cf10629a92324be91d1e243f5a4576b56ad841a5b5942956bafa4b436c99406
|
| 3 |
+
size 29636
|