Instructions to use tlam25/phase1_bert_upsampling_replace_palate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tlam25/phase1_bert_upsampling_replace_palate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tlam25/phase1_bert_upsampling_replace_palate")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tlam25/phase1_bert_upsampling_replace_palate") model = AutoModelForSequenceClassification.from_pretrained("tlam25/phase1_bert_upsampling_replace_palate") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f735fd9afd8a892f69eb4f7e1b62081a0b2cb49cae918513c950c2c3c4ab41bc
- Size of remote file:
- 438 MB
- SHA256:
- 300a7128efc9c0564db5cb977ed7f1ad0b3c37f54e5cfd0077c56dc217d309ab
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