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:
- 6dd70916b32bc4321aae64b68564e309deb28e4a26b5ee8232f4ca51beeab3f9
- Size of remote file:
- 4.54 kB
- SHA256:
- 2b3ef447ca2727f2afbc2dbb209af3e548ff2b33e8b8231aad60214177a533b1
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