Instructions to use marma/bert-base-swedish-cased-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marma/bert-base-swedish-cased-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marma/bert-base-swedish-cased-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marma/bert-base-swedish-cased-sentiment") model = AutoModelForSequenceClassification.from_pretrained("marma/bert-base-swedish-cased-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d93ac9e0581677cbddce2b476a0aacef265298f3656097eb1833ec27628f700b
- Size of remote file:
- 499 MB
- SHA256:
- 7b5408080a57c665b386f50007c0defda35514062920ed939ea60d0311836c08
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