Instructions to use tomlobato/prop_class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tomlobato/prop_class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tomlobato/prop_class")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("tomlobato/prop_class") model = AutoModelForSequenceClassification.from_pretrained("tomlobato/prop_class") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- Mar16_05-11-50_8adb422a7370
- Mar16_05-12-38_8adb422a7370
- Mar16_05-13-12_8adb422a7370
- Mar16_05-17-22_8adb422a7370
- Mar16_05-23-05_8adb422a7370
- Mar16_05-25-15_8adb422a7370
- Mar16_05-43-53_8adb422a7370
- Mar16_05-46-13_8adb422a7370
- Mar16_05-47-29_8adb422a7370
- Mar16_05-49-52_8adb422a7370
- Mar16_05-51-48_8adb422a7370
- Mar16_05-52-44_8adb422a7370
- Mar16_05-55-30_8adb422a7370
- Mar16_05-57-07_8adb422a7370
- Mar16_05-58-05_8adb422a7370
- Mar16_06-01-39_8adb422a7370
- Mar16_06-13-05_8adb422a7370
- Mar16_06-13-25_8adb422a7370
- Mar16_06-14-20_8adb422a7370
- Mar16_06-15-09_8adb422a7370