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:
- d19706e99d0f692e4bca95dc06619d21df82e79dde778fea43a28404a028e5a9
- Size of remote file:
- 4.6 kB
- SHA256:
- b3ee50649c8d9fab73ce0841460adfc0d586b15c1dad1bc44498a373c5893088
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