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--- |
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language: |
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- ru |
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tags: |
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- keywords2poetry |
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- Pushkin |
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- Mayakovsky |
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- Esenin |
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- Blok |
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- Tyutchev |
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--- |
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This repo contains the fune-tuned version of [ai-forever/rugpt3medium_based_on_gpt2](https://huggingface.co./ai-forever/rugpt3medium_based_on_gpt2), which can generate poetry from keywords in style of Pushkin, Mayakovsky, Esenin, Blok and Tyutchev. |
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To use this model, you can do this: |
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``` |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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def generate_poetry(input: str, model, num_beams=3): |
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input = input if len(input) > 0 else tokenizer.bos_token |
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input_ids = tokenizer.encode(input, return_tensors="pt").to(device) |
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# Create an attention mask |
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attention_mask = (input_ids != tokenizer.pad_token_id).float() |
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# Set the pad_token_id |
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tokenizer.pad_token_id = tokenizer.eos_token_id |
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with torch.no_grad(): |
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out = model.generate(input_ids, |
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do_sample=True, |
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num_beams=num_beams, |
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temperature=2.0, |
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top_p=0.9, |
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max_length = 200, |
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eos_token_id=tokenizer.eos_token_id, |
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bos_token_id=tokenizer.bos_token_id, |
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attention_mask=attention_mask |
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).to(device) |
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return tokenizer.batch_decode(out, skip_special_tokens=True)[0] |
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path = 'AnyaSchen/rugpt3-medium-keywords2poetry' |
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tokenizer = AutoTokenizer.from_pretrained(path) |
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model = AutoModelForCausalLM.from_pretrained(path).to(device) |
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inp = 'Автор: Маяковский\nКлючевые слова:<write your keywords>' |
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print(generate_poetry(inp, model)) |
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``` |
