Instructions to use AgroQwertyAI/berta_report_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AgroQwertyAI/berta_report_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AgroQwertyAI/berta_report_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AgroQwertyAI/berta_report_classifier") model = AutoModelForSequenceClassification.from_pretrained("AgroQwertyAI/berta_report_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17dc5708309841871eb08bc5dc6c837e8b425966f1c78a3170133bdcc3f9f85d
- Size of remote file:
- 5.24 kB
- SHA256:
- ca348f03a0a4a626116d87f65ee3f0059ae6181898c36e61b1d80fe6ef9b1945
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