Instructions to use faldeus0092/project_4_transfer_learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faldeus0092/project_4_transfer_learning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="faldeus0092/project_4_transfer_learning") 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("faldeus0092/project_4_transfer_learning") model = AutoModelForImageClassification.from_pretrained("faldeus0092/project_4_transfer_learning") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:73d9d147b55b05d1afddaf7d1d2842d5ec919ffc25f4c24a737ed0a1d640e33f
|
| 3 |
+
size 343242432
|