Instructions to use tweettemposhift/topic-topic_random0_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_random0_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_random0_seed2-bertweet-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random0_seed2-bertweet-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random0_seed2-bertweet-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 016408cf9e42e3808bc284b9917db4c89000a8824f987df453a53cf51bdd8e6d
- Size of remote file:
- 4.54 kB
- SHA256:
- f43beb217feeec61b0a828d12ac349c7f1490517b8a13dabb7ee63030d287fc2
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