Instructions to use badrabbitt/text_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use badrabbitt/text_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="badrabbitt/text_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("badrabbitt/text_classification") model = AutoModelForSequenceClassification.from_pretrained("badrabbitt/text_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ee920971251af65652cab01e78c86080f2edd17a4fae6300b1a20b3ec9e0aeb
- Size of remote file:
- 4.92 kB
- SHA256:
- ab151835502ac5b7523dd9818783f1df64387bd6afeae9d40f627458bffa6961
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