Instructions to use korca/roberta-base-lkm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use korca/roberta-base-lkm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="korca/roberta-base-lkm")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("korca/roberta-base-lkm") model = AutoModel.from_pretrained("korca/roberta-base-lkm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64aa8cb14b1c096e84c0e16e011ad531681a7eaec458092219f0f582fd386857
- Size of remote file:
- 499 MB
- SHA256:
- 823d2cc580d4ad879f3353be0dd736ded764b57f3757e196dec86da8bfb7adc2
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