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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 937ba910f8d18cb14580ad0d08f7f1c54e896d406e043abddfcfc0c5a409532c
- Size of remote file:
- 329 MB
- SHA256:
- 65b9ff404bdfc9f37d1107ca40bf0de68b682429e6a36df1c9328e5a0720d61c
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