Instructions to use KodaPop/begone-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KodaPop/begone-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="KodaPop/begone-model") 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("KodaPop/begone-model") model = AutoModelForImageClassification.from_pretrained("KodaPop/begone-model") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- model.onnx +3 -0
model.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:59075dddf6acc19d005704805bb6e2dcecfa4a63a47276a5b6161d7b808790d5
|
| 3 |
+
size 343573491
|