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--- |
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license: apache-2.0 |
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inference: false |
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--- |
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```python |
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from transformers import AutoTokenizer, AutoModelWithLMHead, AutoModelForCausalLM |
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import torch |
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if torch.cuda.is_available(): |
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device = torch.device("cuda") |
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else : |
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device = "cpu" |
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tokenizer = AutoTokenizer.from_pretrained("Ashishkr/grammar_correction") |
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model = AutoModelForCausalLM.from_pretrained("Ashishkr/grammar_correction").to(device) |
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input_query="what be the reason for everyone leave the company" |
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query= "<|startoftext|> " + input_query + " ~~~" |
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input_ids = tokenizer.encode(query.lower(), return_tensors='pt').to(device) |
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sample_outputs = model.generate(input_ids, |
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do_sample=True, |
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num_beams=1, |
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max_length=128, |
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temperature=0.9, |
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top_p= 0.7, |
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top_k = 5, |
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num_return_sequences=3) |
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corrected_sentences = [] |
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for i in range(len(sample_outputs)): |
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r = tokenizer.decode(sample_outputs[i], skip_special_tokens=True).split('||')[0] |
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r = r.split('~~~')[1] |
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if r not in corrected_sentences: |
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corrected_sentences.append(r) |
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print(corrected_sentences) |
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``` |
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