Instructions to use dsaint31/tmp-pl-image-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dsaint31/tmp-pl-image-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dsaint31/tmp-pl-image-classification") 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("dsaint31/tmp-pl-image-classification") model = AutoModelForImageClassification.from_pretrained("dsaint31/tmp-pl-image-classification") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -10,8 +10,6 @@ tags:
|
|
| 10 |
license: apache-2.0
|
| 11 |
datasets:
|
| 12 |
- ILSVRC/imagenet-1k
|
| 13 |
-
language:
|
| 14 |
-
- ko
|
| 15 |
base_model:
|
| 16 |
- google/vit-base-patch16-224
|
| 17 |
pipeline_tag: image-classification
|
|
@@ -269,4 +267,4 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
|
|
| 269 |
|
| 270 |
## Model Card Contact
|
| 271 |
|
| 272 |
-
* Hugging Face profile: [https://huggingface.co/dsaint31](https://huggingface.co/dsaint31)
|
|
|
|
| 10 |
license: apache-2.0
|
| 11 |
datasets:
|
| 12 |
- ILSVRC/imagenet-1k
|
|
|
|
|
|
|
| 13 |
base_model:
|
| 14 |
- google/vit-base-patch16-224
|
| 15 |
pipeline_tag: image-classification
|
|
|
|
| 267 |
|
| 268 |
## Model Card Contact
|
| 269 |
|
| 270 |
+
* Hugging Face profile: [https://huggingface.co/dsaint31](https://huggingface.co/dsaint31)
|