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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ecb0b6152e79a0e26e2411f521a9a750106e1b89664faf388e1aabc5161c9e77
- Size of remote file:
- 499 MB
- SHA256:
- 459fc7c65626857fcc64baf0e3f325227c130a0a0d7f460dcd8be669278e2ff2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.