Instructions to use 24bean/multi_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 24bean/multi_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="24bean/multi_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("24bean/multi_classification") model = AutoModelForSequenceClassification.from_pretrained("24bean/multi_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fb6c8ba35999a6b4a9243ce0ef6174a62a0278757f69370fafcde95876c1fe1
- Size of remote file:
- 498 MB
- SHA256:
- f85daee7cd9464bf106e98c75531e75848ff7016f888a8e4fee540a51d967e89
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.