Instructions to use kazzand/ru-longformer-tiny-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kazzand/ru-longformer-tiny-16384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kazzand/ru-longformer-tiny-16384")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("kazzand/ru-longformer-tiny-16384") model = AutoModelForMaskedLM.from_pretrained("kazzand/ru-longformer-tiny-16384", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from kazzand/ru-longformer-tiny-16384: direct link, hf CLI and curl.
- Browser
- Download file 2.41 MB
-
https://huggingface.co/kazzand/ru-longformer-tiny-16384/resolve/main/tokenizer.json
- Command line
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hf download hf://kazzand/ru-longformer-tiny-16384/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/kazzand/ru-longformer-tiny-16384/resolve/main/tokenizer.json
2.41 MB
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