Instructions to use ppsingh/mpnet-multilabel-sector-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ppsingh/mpnet-multilabel-sector-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ppsingh/mpnet-multilabel-sector-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ppsingh/mpnet-multilabel-sector-classifier") model = AutoModelForSequenceClassification.from_pretrained("ppsingh/mpnet-multilabel-sector-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2797dc18cbba4fd61e9e942d6d8d4de97f7f1470dbfdb6edbc2f417ab0355bf7
- Size of remote file:
- 438 MB
- SHA256:
- 6e4da4eecf1cf32c2a069cffc79152b2a40c00f0fb16a9d3462fa1cb43477c83
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