Image Classification
Transformers
PyTorch
TensorBoard
beit
Generated from Trainer
Eval Results (legacy)
Instructions to use ChasingMercer/weather-mod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChasingMercer/weather-mod with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ChasingMercer/weather-mod") 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("ChasingMercer/weather-mod") model = AutoModelForImageClassification.from_pretrained("ChasingMercer/weather-mod", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 210 Bytes
b3efbb1 | 1 2 3 4 5 6 7 8 | {
"epoch": 6.0,
"total_flos": 1.7589230025365053e+18,
"train_loss": 0.10344488720941004,
"train_runtime": 2153.5363,
"train_samples_per_second": 10.506,
"train_steps_per_second": 0.329
} |