Instructions to use tweettemposhift/topic-topic_random3_seed1-roberta-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-roberta-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-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random3_seed1-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random3_seed1-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e68213707637afdfa9b0ad2b8ca4f1090c94baac34fd1623cdcd4e99b56b51fa
- Size of remote file:
- 4.54 kB
- SHA256:
- dafb96af55800f30724f0454a73cb174cec9bbd4c71e1e93702189b73f9b8705
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.