Instructions to use franfj/DIPROMATS_subtask_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use franfj/DIPROMATS_subtask_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="franfj/DIPROMATS_subtask_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("franfj/DIPROMATS_subtask_2") model = AutoModelForSequenceClassification.from_pretrained("franfj/DIPROMATS_subtask_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d327f32d2b740f0fba0f4e2d14742c3c790e58a8cf72739b80d4c926d9191060
- Size of remote file:
- 329 MB
- SHA256:
- f5b30cfafbb4f481222e80c66efba4e47deb2e0351295b46da5188a1372d6b87
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