Instructions to use EMBEDDIA/sloberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EMBEDDIA/sloberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="EMBEDDIA/sloberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("EMBEDDIA/sloberta") model = AutoModelForMaskedLM.from_pretrained("EMBEDDIA/sloberta", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from EMBEDDIA/sloberta: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/EMBEDDIA/sloberta/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://EMBEDDIA/sloberta/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/EMBEDDIA/sloberta/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- ee80bc5fccf5ca6981bd1338804a8e3c5ce73f2926e78133dbf64c71bfabd1cd
- Size of remote file:
- 443 MB
- SHA256:
- 70e8b17911d314d02e1f7d47ad4fb47d1c3dd725ac73256b08cbab0f9c3cb809
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