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 tokenizer.json from EMBEDDIA/sloberta: direct link, hf CLI and curl.
- Browser
- Download file 1.65 MB
-
https://huggingface.co/EMBEDDIA/sloberta/resolve/main/tokenizer.json
- Command line
-
hf download hf://EMBEDDIA/sloberta/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/EMBEDDIA/sloberta/resolve/main/tokenizer.json
1.65 MB
File too large to display, you can check the raw version instead.