Instructions to use tweettemposhift/topic-topic_temporal-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/topic-topic_temporal-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/topic-topic_temporal-roberta-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_temporal-roberta-large") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_temporal-roberta-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 513c6a420331b68f183b15102ab17c338c2cd13b2ed65314cd134eb900319e67
- Size of remote file:
- 1.42 GB
- SHA256:
- 0f7440bafa850e8be3a6e7aef2c86346ed9a32e2790d2446c2a9fadb0e777c41
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.