Instructions to use tommilyjones/vit-base-patch16-224-finetuned-masked-hateful-meme-restructured with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tommilyjones/vit-base-patch16-224-finetuned-masked-hateful-meme-restructured with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tommilyjones/vit-base-patch16-224-finetuned-masked-hateful-meme-restructured") 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("tommilyjones/vit-base-patch16-224-finetuned-masked-hateful-meme-restructured") model = AutoModelForImageClassification.from_pretrained("tommilyjones/vit-base-patch16-224-finetuned-masked-hateful-meme-restructured", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
c1f4289
1
Parent(s): 9d5dcdf
End of training
Browse files- all_results.json +8 -0
- eval_results.json +8 -0
all_results.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"epoch": 9.92,
|
| 3 |
+
"eval_accuracy": 0.54,
|
| 4 |
+
"eval_loss": 0.7518242001533508,
|
| 5 |
+
"eval_runtime": 4.7587,
|
| 6 |
+
"eval_samples_per_second": 105.071,
|
| 7 |
+
"eval_steps_per_second": 3.362
|
| 8 |
+
}
|
eval_results.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"epoch": 9.92,
|
| 3 |
+
"eval_accuracy": 0.54,
|
| 4 |
+
"eval_loss": 0.7518242001533508,
|
| 5 |
+
"eval_runtime": 4.7587,
|
| 6 |
+
"eval_samples_per_second": 105.071,
|
| 7 |
+
"eval_steps_per_second": 3.362
|
| 8 |
+
}
|