Instructions to use Silly-Machine/TuPy_BERT_e3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Silly-Machine/TuPy_BERT_e3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Silly-Machine/TuPy_BERT_e3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Silly-Machine/TuPy_BERT_e3") model = AutoModelForSequenceClassification.from_pretrained("Silly-Machine/TuPy_BERT_e3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53488a0351c43bebc1bde3dd4d93420e4b083392493fa35ae49a9eaebb7b964e
- Size of remote file:
- 436 MB
- SHA256:
- f624cc409884e3f0a883e6911a82b5d13cb4df65d37c6b34bdff5560a687f3ff
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