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:
- 5a6b7add250c6b1ab22dc5a7c4582934af9317fabf77741bd93b9e9e6959e196
- Size of remote file:
- 329 MB
- SHA256:
- ff607495c2ca262da3d6f15a0ec38738d6e9dd3a74c4b5e60cdc6eef7a83d4f4
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