Instructions to use Cameron/BERT-SBIC-targetcategory with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cameron/BERT-SBIC-targetcategory with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cameron/BERT-SBIC-targetcategory")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cameron/BERT-SBIC-targetcategory") model = AutoModelForSequenceClassification.from_pretrained("Cameron/BERT-SBIC-targetcategory") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 594f0fb016b2d527f02b3e98dc773e52f4973ee504662a136f7f19cc66d4587b
- Size of remote file:
- 2.35 kB
- SHA256:
- 4c16e94b626c6d088f9c6a0189b96f387c1f4d290bbfb9dc96d91a3e6acf8491
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