Instructions to use tweettemposhift/topic-topic_random2_seed2-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/topic-topic_random2_seed2-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/topic-topic_random2_seed2-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random2_seed2-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random2_seed2-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f25308d6f77f5d63c8ce9dca45686e7dc58e8ef5b6d26ce3f1d928a38866cf6
- Size of remote file:
- 499 MB
- SHA256:
- fd59f84f683ade2facd220fefca55c6768348444cfcca01e3256a126ddd60692
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.