Instructions to use tartuNLP/EstBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tartuNLP/EstBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tartuNLP/EstBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tartuNLP/EstBERT") model = AutoModelForMaskedLM.from_pretrained("tartuNLP/EstBERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from tartuNLP/EstBERT: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/tartuNLP/EstBERT/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://tartuNLP/EstBERT/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/tartuNLP/EstBERT/resolve/main/flax_model.msgpack
498 MB
- Xet hash:
- 6a6fff698b9f23677021924c5d25c1ccbc58d453d0548edec3d713581dd8ba81
- Size of remote file:
- 498 MB
- SHA256:
- 4ac4609e43482f877489959878361e488f1fcf510c2317a04c7d637f4ec4fe23
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