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+ # Math-RoBerta for NLP tasks in math learning environments
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+
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+ This model is fine-tuned with GPT-xl with over 3,000,000 posts and replies from students and instructors in Algebra Nation (https://www.mathnation.com/). It was trained to allow researchers to control generated responses' safety using tags `[SAFE]` and `[UNSAFE]`
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+
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+ ### Here is how to use it with texts in HuggingFace
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+ ```python
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+ # A list of special tokens the model was trained with
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+ special_tokens_dict = {
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+ 'additional_special_tokens': [
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+ '[SAFE]','[UNSAFE]', '[OK]', '[SELF_M]','[SELF_F]', '[SELF_N]',
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+ '[PARTNER_M]', '[PARTNER_F]', '[PARTNER_N]',
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+ '[ABOUT_M]', '[ABOUT_F]', '[ABOUT_N]', '<speaker1>', '<speaker2>'
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+ ],
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+ 'bos_token': '<bos>',
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+ 'eos_token': '<eos>',
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+ }
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+
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+ from transformers import AutoTokenizer, AutoModelForCausalLM
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+
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+ math_bot_tokenizer = AutoTokenizer.from_pretrained('uf-aice-lab/SafeMathBot')
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+ safe_math_bot = AutoModelForCausalLM.from_pretrained('uf-aice-lab/SafeMathBot')
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+ text = "Replace me by any text you'd like."
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+ encoded_input = math_bot_tokenizer(text, return_tensors='pt')
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+ output = safe_math_bot(**encoded_input)
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+ ```