Text Classification
Transformers
PyTorch
English
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use badalsahani/text-classification-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use badalsahani/text-classification-multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="badalsahani/text-classification-multi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("badalsahani/text-classification-multi") model = AutoModelForSequenceClassification.from_pretrained("badalsahani/text-classification-multi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63ce4cbd2458c1dd63630e62f1bbff3c8677a3124d2e0440f32ef06ffd12a66d
- Size of remote file:
- 1.33 GB
- SHA256:
- d30aa4d406bae7af0d328f05624b45e3e2fea3c7d0ca5d67c2e9e3067af7cf6f
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