Instructions to use simant/roberta-sector-tag-classification-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simant/roberta-sector-tag-classification-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="simant/roberta-sector-tag-classification-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("simant/roberta-sector-tag-classification-v2") model = AutoModelForSequenceClassification.from_pretrained("simant/roberta-sector-tag-classification-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 099bb4519737afb0742eb2552a88cd016ca4cc42335674dbdfdb6446bad8845b
- Size of remote file:
- 499 MB
- SHA256:
- 9a1941afb37d90c1eae2e5c5e370a4186f9b8689b813e40a9ce3f625f87a94e0
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