Instructions to use tweettemposhift/topic-topic_random1_seed2-bernice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/topic-topic_random1_seed2-bernice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/topic-topic_random1_seed2-bernice")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random1_seed2-bernice") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random1_seed2-bernice") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a221b7394d27a9ba0a04ab629bf653e83bc34361d31e944cefbd01b60eca8149
- Size of remote file:
- 1.11 GB
- SHA256:
- 985c38a7bc4dbd0fdd136db28fdc1fbfb5bd3a1704d24c22771d56dc80142556
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