Instructions to use tweettemposhift/topic-topic_random2_seed1-bertweet-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/topic-topic_random2_seed1-bertweet-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/topic-topic_random2_seed1-bertweet-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random2_seed1-bertweet-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random2_seed1-bertweet-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 097f38e6dc9d618567c871c34a6f79857419c2f1c9f040ba26cc934c5e98534e
- Size of remote file:
- 540 MB
- SHA256:
- 0bdeb4229d4a005ce210ba7438b1cf09997d56586ebc9b3f9d4fb55042450015
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