Instructions to use tweettemposhift/topic-topic_random2_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_random2_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_random2_seed2-bertweet-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random2_seed2-bertweet-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random2_seed2-bertweet-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b40aa57654b49c118b92a2e3ad5210949badf6d682d0fb688bc6b56e9c44051a
- Size of remote file:
- 4.54 kB
- SHA256:
- 644aa5ca0db973b9a76c1694962d11243b2e07c98652756e229b25bfa2068fa6
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