Instructions to use tweettemposhift/topic-topic_random3_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_random3_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_random3_seed2-bertweet-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random3_seed2-bertweet-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random3_seed2-bertweet-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c567ec8d7e9de2af06cf08204e08369f538bbf6f4c4954683225f76434d35bf
- Size of remote file:
- 540 MB
- SHA256:
- 72dab2fe0cbcbecdae7b1d46b1c9f0a875b4a1b031628eff376dbdd97efb11b5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.