Instructions to use franfj/DIPROMATS_subtask_3_group4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use franfj/DIPROMATS_subtask_3_group4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="franfj/DIPROMATS_subtask_3_group4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("franfj/DIPROMATS_subtask_3_group4") model = AutoModelForSequenceClassification.from_pretrained("franfj/DIPROMATS_subtask_3_group4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 158ac2238254cf12ca9b295069d560f7fd409cd95f719b0241813668145d288f
- Size of remote file:
- 328 MB
- SHA256:
- b8f239bb8bbfaeee38df52f6e7ca06dbacfeac04fb92f82af6936335a93fc305
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