Instructions to use tweettemposhift/topic-topic_random1_seed2-bertweet-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/topic-topic_random1_seed2-bertweet-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/topic-topic_random1_seed2-bertweet-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random1_seed2-bertweet-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random1_seed2-bertweet-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 676df8b0f152bb31d14db830b892e93df5dd96d51c0ae3729333ec3ab423a3d3
- Size of remote file:
- 4.54 kB
- SHA256:
- fcf048f95df62ba372c68bcdf56604499441ca2d02c43cd6e5356c5871360f84
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