Instructions to use tlam25/phase1_bert_upsampling_replace_taste with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tlam25/phase1_bert_upsampling_replace_taste with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tlam25/phase1_bert_upsampling_replace_taste")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tlam25/phase1_bert_upsampling_replace_taste") model = AutoModelForSequenceClassification.from_pretrained("tlam25/phase1_bert_upsampling_replace_taste") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3f1fb9a0e9c705a03fc38f3e3cb5f2dc193f672755d3970fc04e4a27194fe0d
- Size of remote file:
- 438 MB
- SHA256:
- 3f997489ac9434029cf5de23dfe5388fc29d499018ccd55be17eba63db823212
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