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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71c51877968b6c4c31f380003c85427bd7c1c2b44316c089378acc7f4d5c969c
- Size of remote file:
- 1.34 GB
- SHA256:
- d3ee552c233b8c07c45ca5729dd1341a091ab26349c57812829536c210a5b7a0
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