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 17
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 13346069
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6d8869b9e2fd02ff4d4b5e869dfa0ac8e97584c711c269cbbf4248d054454175
|
| 3 |
size 13346069
|
runs/Jul10_18-44-31_teesta/events.out.tfevents.1688994879.teesta.6977.0
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 sha256:90701a016fff81058ac361454d67cf0d029f3c146acb5bdee86dddcb71215e33
|
| 3 |
+
size 12901
|