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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 14
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 343268717
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:539fe700d8f663c89b1b921b69c45dd3752b0c91e5e2980bd82feddd0c246276
|
| 3 |
size 343268717
|
runs/Jul11_19-56-05_teesta/events.out.tfevents.1689085573.teesta.24348.0
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:ddd2dfd913ed47e89a44d3f88b16c1de9893d1f74e63ab7d4dfcd0ecbfe66860
|
| 3 |
+
size 11055
|