Instructions to use franfj/DIPROMATS_subtask_3_group2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use franfj/DIPROMATS_subtask_3_group2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="franfj/DIPROMATS_subtask_3_group2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("franfj/DIPROMATS_subtask_3_group2") model = AutoModelForSequenceClassification.from_pretrained("franfj/DIPROMATS_subtask_3_group2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a59e441370bbfd2de557749fc1820f84f4034adc2922b75c0bf77d2a0335c2a
- Size of remote file:
- 329 MB
- SHA256:
- e0b4e403f36016ad0e611d1b19c99d795e31f5a2e25233399e026f222dd64c0c
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