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---
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license: afl-3.0
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---
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# Docto Bot
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## Usage (HuggingFace Transformers)
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```
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pip install -U transformers
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```
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```python
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import random
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("docto/Docto-Bot")
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model = AutoModelForCausalLM.from_pretrained("docto/Docto-Bot")
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special_token = '<|endoftext|>'
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prompt_text = 'Question: I am having fever\nAnswer:'
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#prompt_text = f'Question: {userinput}\nAnswer:'
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encoded_prompt = tokenizer.encode(prompt_text,
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add_special_tokens = False,
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return_tensors = 'pt')
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output_sequences = model.generate(
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input_ids = encoded_prompt,
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max_length = 700,
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temperature = 0.9,
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top_k = 20,
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top_p = 0.9,
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repetition_penalty = 1,
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do_sample = True,
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num_return_sequences = 4
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)
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result = tokenizer.decode(random.choice(output_sequences))
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result = result[result.index("Answer: "):result.index(special_token)]
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print(result[8:])
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```
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## Training Data
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The Docto-Bot was trained on [Medical Question/Answer dataset](https://github.com/LasseRegin/medical-question-answer-data) |
