Instructions to use tweettemposhift/topic-topic_random0_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_random0_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_random0_seed1-bertweet-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random0_seed1-bertweet-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random0_seed1-bertweet-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4e35e5a1b84afea8bd0aee926e11d39de7fedbf24ab9888bef469626242b273
- Size of remote file:
- 540 MB
- SHA256:
- 668b1582b106150301d620d00e6bf0be7ebf05114ddc392502f90d4e8b9c3af6
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