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:
- 546caa94a40c030a7cfa424aaa9b039ca3e5a4b1d12973d817357cdd4ce5c603
- Size of remote file:
- 433 MB
- SHA256:
- 8b7b71e13930bed1dc8dde9a0aaa89612c6bbc5fe4cac59ca8b25e7e3e340d3a
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