Instructions to use badrabbitt/text_classification_bert_340 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use badrabbitt/text_classification_bert_340 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="badrabbitt/text_classification_bert_340")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("badrabbitt/text_classification_bert_340") model = AutoModelForSequenceClassification.from_pretrained("badrabbitt/text_classification_bert_340") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ecec2bd8c40a8371de69dced472f03e2c77787e76bad82c8cb117ec4a192c17c
- Size of remote file:
- 4.98 kB
- SHA256:
- 0309eae08e4cd67dfdeeb730f41d2642feb48a6a02b8518aba40261e5cd553b3
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