Instructions to use mrm8488/RuPERTa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/RuPERTa-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mrm8488/RuPERTa-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/RuPERTa-base") model = AutoModelForMaskedLM.from_pretrained("mrm8488/RuPERTa-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from mrm8488/RuPERTa-base: direct link, hf CLI and curl.
- Browser
- Download file 504 MB
-
https://huggingface.co/mrm8488/RuPERTa-base/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://mrm8488/RuPERTa-base/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/mrm8488/RuPERTa-base/resolve/main/flax_model.msgpack
504 MB
- Xet hash:
- 963746da8990590b564006df7e3d69ea3b8d90edc2e03ca9e4c426046f25a801
- Size of remote file:
- 504 MB
- SHA256:
- 0dbe4e9f5bc35d5c2255774623e8606ce4bc98a176d61819f61166452f69d46d
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