Instructions to use Manu9000k/finetuned_bert_4_classifications with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Manu9000k/finetuned_bert_4_classifications with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Manu9000k/finetuned_bert_4_classifications")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Manu9000k/finetuned_bert_4_classifications") model = AutoModelForSequenceClassification.from_pretrained("Manu9000k/finetuned_bert_4_classifications") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5dbc86246dee02d7bd6b15788e8639b1a305de12e4144deeb6a8a7c72264a6d8
- Size of remote file:
- 4.6 kB
- SHA256:
- 1c8f3968704bf1e3254122dae54aa9760446d3be048c43ce726e09ffecd3379b
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