Instructions to use tomashs/cowese_binarycls_beto_top2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tomashs/cowese_binarycls_beto_top2vec with Transformers:
# Load model directly from transformers import AutoTokenizer, BertForSequenceClassificationWithTopics tokenizer = AutoTokenizer.from_pretrained("tomashs/cowese_binarycls_beto_top2vec") model = BertForSequenceClassificationWithTopics.from_pretrained("tomashs/cowese_binarycls_beto_top2vec", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c3968d519c040af3da4717be541d6e7f975b75c49afc54672551f48de82c23c
- Size of remote file:
- 439 MB
- SHA256:
- 29bd78a4bc6188c9b12447cbdb5001694208e4a8a57e05df2519a4581b166933
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