Instructions to use tweettemposhift/topic-topic_random0_seed1-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/topic-topic_random0_seed1-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/topic-topic_random0_seed1-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random0_seed1-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random0_seed1-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45a621c999577e6c6b799dfe96a8e1e1dca08f90dd18b02fa4869bf0a9f0711f
- Size of remote file:
- 499 MB
- SHA256:
- 7272c0299b687374932e60f444f7329ba49bb21eb8b2d54aafdec8b3e095f428
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