Fill-Mask
Transformers
ONNX
Safetensors
Bashkir
bashkir-roberta-preln
bashkir
masked-language-modeling
roberta
sentencepiece
custom-code
onnxruntime
custom_code
Instructions to use failed09/bashkir-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use failed09/bashkir-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="failed09/bashkir-roberta", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("failed09/bashkir-roberta", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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## License
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The model weights, tokenizer and release code are distributed under the
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[Apache-2.0 license](LICENSE). Training texts are not redistributed; their
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rights remain with their respective owners. For provenance or removal requests,
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contact the maintainer through the Hub.
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## License
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The model weights, tokenizer and release code are distributed under the
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[Apache-2.0 license](https://huggingface.co/failed09/bashkir-roberta/blob/main/LICENSE). Training texts are not redistributed; their
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rights remain with their respective owners. For provenance or removal requests,
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contact the maintainer through the Hub.
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e9f179aad7619153724920c86a90ecc3c161fd15ffc3332f200e9f2073a07f72 configuration_bashkir_roberta.py
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cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30 LICENSE
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