Instructions to use MaagDeveloper/rust_python_roberta_base_mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MaagDeveloper/rust_python_roberta_base_mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="MaagDeveloper/rust_python_roberta_base_mlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("MaagDeveloper/rust_python_roberta_base_mlm") model = AutoModelForMaskedLM.from_pretrained("MaagDeveloper/rust_python_roberta_base_mlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer
Browse files- tokenizer_config.json +2 -0
tokenizer_config.json
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"backend": "tokenizers",
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"bos_token": "<s>",
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"eos_token": "</s>",
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"mask_token": "<mask>",
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"model_input_names": [
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"input_ids",
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"backend": "tokenizers",
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"bos_token": "<s>",
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"eos_token": "</s>",
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"is_local": false,
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"local_files_only": false,
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"mask_token": "<mask>",
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"model_input_names": [
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"input_ids",
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