frncscp/patacon-730
Viewer • Updated • 1.46k • 67
How to use frncscp/patacoptimus-prime with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="frncscp/patacoptimus-prime")
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("frncscp/patacoptimus-prime")
model = AutoModelForImageClassification.from_pretrained("frncscp/patacoptimus-prime")This model is a fine-tuned version of google/vit-base-patch16-224-in21k on frncscp/patacon-730. It achieves the following results on the evaluation set:
One-Class Patacognition Transformer
It was designed for One-Class Patacón Classification
More information needed
The following hyperparameters were used during training:
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|---|---|---|---|
| 0.0064 | 0.0079 | 0.9977 | 0 |
| 0.0043 | 0.0086 | 0.9977 | 1 |