Instructions to use franfj/DIPROMATS_subtask_3_group1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use franfj/DIPROMATS_subtask_3_group1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="franfj/DIPROMATS_subtask_3_group1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("franfj/DIPROMATS_subtask_3_group1") model = AutoModelForSequenceClassification.from_pretrained("franfj/DIPROMATS_subtask_3_group1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a3d40553890f73683738b0fc2657af64fa3f0b7b55e52f0bfc6d18587912a4d
- Size of remote file:
- 328 MB
- SHA256:
- a174bf994479825d76d0a3931118c170c39e54d07a4dfd67838bb9ad3c902617
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