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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 813628e4ad1aac210c0719b4ad57d111e90eea3647ad7a0dd78e486921479782
- Size of remote file:
- 438 MB
- SHA256:
- 4befa2b60670707dcb6a00fe3937447c4a51572c785b60eaddff115eacaf52a4
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