Instructions to use Babak-Behkamkia/bert_VAST_long3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Babak-Behkamkia/bert_VAST_long3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Babak-Behkamkia/bert_VAST_long3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Babak-Behkamkia/bert_VAST_long3") model = AutoModelForSequenceClassification.from_pretrained("Babak-Behkamkia/bert_VAST_long3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2cea530e146a45e420bc23f2fbd7cfd828f20ba4bba6301858c3cc8955005fca
- Size of remote file:
- 433 MB
- SHA256:
- f30106eec524ab83773d3fc530807db70c74d8bdbcb888f10d51fd9ac92e1f09
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