Instructions to use tweettemposhift/topic-topic_random3_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_random3_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_random3_seed1-bertweet-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random3_seed1-bertweet-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random3_seed1-bertweet-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a1fa55a00ae21ac839e16ae293a18919244ea111a11c6fa66116a7e77f75a12
- Size of remote file:
- 540 MB
- SHA256:
- 82365655fc4ec4a20cecc952e16dc7042de5d35646840e12a47932b893478b0a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.