Instructions to use Finnish-NLP/convbert-base-finnish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Finnish-NLP/convbert-base-finnish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Finnish-NLP/convbert-base-finnish")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Finnish-NLP/convbert-base-finnish") model = AutoModel.from_pretrained("Finnish-NLP/convbert-base-finnish") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9beb4948ef87ac127e41a1ffe99a3c1a21daee5e6f7cee9cb9c033621b8769c6
- Size of remote file:
- 483 MB
- SHA256:
- 4dec5473cc9fed3c62d06e25247ccffdeac12c8903f9f63d22f718f0b2977964
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.