Instructions to use mpapucci/bert-gender-classification-tag-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpapucci/bert-gender-classification-tag-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mpapucci/bert-gender-classification-tag-it")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mpapucci/bert-gender-classification-tag-it") model = AutoModelForSequenceClassification.from_pretrained("mpapucci/bert-gender-classification-tag-it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc91c18eb928fb6fbe02e1e339b9eaead62861832f8a205301c451df3261cc79
- Size of remote file:
- 440 MB
- SHA256:
- 84c24c4ff702db6d538615a43d3fc62584174bf1a0b53c9d9a13f5fb7215f808
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