Instructions to use ardha27/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ardha27/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ardha27/image_classification") 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("ardha27/image_classification") model = AutoModelForImageClassification.from_pretrained("ardha27/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 41
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 343242432
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:04586c08e6f3fad0cf109d8efdc5231183ff64e28aac439297ed2d7f90692eda
|
| 3 |
size 343242432
|
runs/Feb16_06-05-29_e992295273e3/events.out.tfevents.1708063530.e992295273e3.1239.1
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 sha256:8995cce15df8200b6fbe09aca3765162b32c3f7045e4418782834ad805516ec4
|
| 3 |
+
size 18257
|