Instructions to use franfj/DIPROMATS_subtask_3_group4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use franfj/DIPROMATS_subtask_3_group4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="franfj/DIPROMATS_subtask_3_group4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("franfj/DIPROMATS_subtask_3_group4") model = AutoModelForSequenceClassification.from_pretrained("franfj/DIPROMATS_subtask_3_group4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e56c2acbe405b544961f8e6f4d078454808145daf09e79c2a844fab1358f077
- Size of remote file:
- 329 MB
- SHA256:
- 5f40b517b5a0299dd62abfc2a08cfa9e92f9a7d59d5b577ba1bf3331673cc258
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