Instructions to use psaegert/nlinec-D-coarse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use psaegert/nlinec-D-coarse with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="psaegert/nlinec-D-coarse")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("psaegert/nlinec-D-coarse") model = AutoModelForSequenceClassification.from_pretrained("psaegert/nlinec-D-coarse", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1bc2395f76344a505ab3192a3dffb8f7081f1ac1793ac75657a562280ac289d
- Size of remote file:
- 3.45 kB
- SHA256:
- 6f4e241c80c5aa8018f9dc43e76be8b31e83384172f61ed5522cedb9e4d978d0
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