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README.md ADDED
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+ ---
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+ language: "en"
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+ tags:
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+ - grammar
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+ - text-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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+
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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).
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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
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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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+ result = happy_tt.generate_text("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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+ {
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+ "_name_or_path": "t5-base",
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+ "architectures": [
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+ "T5ForConditionalGeneration"
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+ ],
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+ "d_ff": 3072,
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+ "d_kv": 64,
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+ "d_model": 768,
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+ "decoder_start_token_id": 0,
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+ "dropout_rate": 0.1,
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+ "eos_token_id": 1,
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+ "feed_forward_proj": "relu",
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+ "gradient_checkpointing": false,
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+ "initializer_factor": 1.0,
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+ "is_encoder_decoder": true,
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+ "layer_norm_epsilon": 1e-06,
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+ "model_type": "t5",
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+ "n_positions": 512,
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+ "num_decoder_layers": 12,
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+ "num_heads": 12,
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+ "num_layers": 12,
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+ "output_past": true,
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+ "pad_token_id": 0,
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+ "relative_attention_num_buckets": 32,
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+ "task_specific_params": {
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+ "summarization": {
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+ "early_stopping": true,
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+ "length_penalty": 2.0,
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+ "max_length": 200,
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+ "min_length": 30,
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+ "no_repeat_ngram_size": 3,
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+ "num_beams": 4,
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+ "prefix": "summarize: "
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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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+ "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 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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