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:
- 9fbb74f63eb8d48de3dc50c9dcc01c34f8df3e90a0537b1c04821072e149448f
- Size of remote file:
- 540 MB
- SHA256:
- d731dd242b49417bb27e21c28363290a965dce773ce1855159f378a517ff6981
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