Instructions to use tartuNLP/EstBERT_512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tartuNLP/EstBERT_512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tartuNLP/EstBERT_512")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tartuNLP/EstBERT_512") model = AutoModelForMaskedLM.from_pretrained("tartuNLP/EstBERT_512", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tartuNLP/EstBERT_512: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/tartuNLP/EstBERT_512/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tartuNLP/EstBERT_512/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tartuNLP/EstBERT_512/resolve/main/pytorch_model.bin
498 MB
- Xet hash:
- 974ea23ac9ce3448b28a758090e0e5b15f6a0f3ab86265dff08d0fcf60a78abd
- Size of remote file:
- 498 MB
- SHA256:
- 7e71d320cc2154eab36e83cb5dc867c19c873f731271f5b49b39c5b49b79a525
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