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README.md CHANGED
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  ---
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- license: apache-2.0
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ language: en
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+ tags:
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+ - grammar
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+ - text2text-generation
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+ license: cc-by-nc-sa-4.0
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+ datasets:
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+ - jfleg
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  ---
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+
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+ # T5 Grammar Correction
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+
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+ This model generates a revised version of inputted text with the goal of containing fewer grammatical errors.
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+ It was trained with [Happy Transformer](https://github.com/EricFillion/happy-transformer)
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+ using a dataset called [JFLEG](https://arxiv.org/abs/1702.04066). Here's a [full article](https://www.vennify.ai/fine-tune-grammar-correction/) on how to train a similar model.
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+
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+
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+ ## Usage
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+
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+ `pip install happytransformer `
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+
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+ ```python
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+ from happytransformer import HappyTextToText, TTSettings
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+
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+ happy_tt = HappyTextToText("T5", "vennify/t5-base-grammar-correction")
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+
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+ args = TTSettings(num_beams=5, min_length=1)
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+
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+ # Add the prefix "grammar: " before each input
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+ result = happy_tt.generate_text("grammar: This sentences has has bads grammar.", args=args)
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+
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+ print(result.text) # This sentence has bad grammar.
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+
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+
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+ ```
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+ "_name_or_path": "t5-base",
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+ "T5ForConditionalGeneration"
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+ ],
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+ },
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+ "translation_en_to_de": {
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+ "early_stopping": true,
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+ "max_length": 300,
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+ "num_beams": 4,
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+ "prefix": "translate English to German: "
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+ },
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+ "translation_en_to_fr": {
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+ "early_stopping": true,
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+ "max_length": 300,
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+ "num_beams": 4,
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+ "prefix": "translate English to French: "
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+ },
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+ "translation_en_to_ro": {
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+ "prefix": "translate English to Romanian: "
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+ }
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+ },
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.9.2",
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+ "use_cache": true,
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+ "vocab_size": 32128
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+ }
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