Instructions to use Babak-Behkamkia/bert_VAST_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Babak-Behkamkia/bert_VAST_binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Babak-Behkamkia/bert_VAST_binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Babak-Behkamkia/bert_VAST_binary") model = AutoModelForSequenceClassification.from_pretrained("Babak-Behkamkia/bert_VAST_binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1c17d8722ef7a0acb3cfc6e48bec791bafb6c3eed5cb665ecc766a2e1002806
- Size of remote file:
- 433 MB
- SHA256:
- b310fd381d9d8921aadebc310085432b4d706b95a07f5c13d5336b1ef8129d66
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