Instructions to use tweettemposhift/topic-topic_temporal-bernice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/topic-topic_temporal-bernice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/topic-topic_temporal-bernice")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_temporal-bernice") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_temporal-bernice") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f49e6542e9a6b620bafe739823aefc4755f7593540ec3634fe97ce00bc28d92a
- Size of remote file:
- 4.54 kB
- SHA256:
- 5591ee6c3f869b3778705853285b9add078fcfe0f305f62535ba25529e65c096
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