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--- |
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language: en |
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tags: |
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- ELI5 |
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license: gpl-3.0 |
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datasets: |
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- eli5 |
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Task: Summarization |
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widget: |
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- text: "<|BOS|><|SEP|>Consulting,business,Fraud<|SEP|>" |
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inference: |
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parameters: |
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temperature: 0.9 |
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return_full_text: False |
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repetition_penalty: 1 |
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--- |
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# Conditional ELI5 Generator |
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Given a few keywords, it generates an Eli5 question with a corresponding answer. |
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The model is mainly used for [SeemsPhishy](https://github.com/madhour/seemsphishy) to auto generate newsletters for phishing/penetration-testing. |
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# How to use |
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```Python |
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from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM |
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from torch import tensor |
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tokenizer = AutoTokenizer.from_pretrained("Madhour/gpt2-eli5") |
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model = AutoModelForCausalLM.from_pretrained("Madhour/gpt2-eli5") |
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prompt = <|BOS|> +"I have a question."+ <|SEP|> + "keyword1,keyword2,keyword3" + <|SEP|> |
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prompt = tensor(tokenizer.encode(prompt)).unsqueeze(0) |
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text = model.generate(prompt, |
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do_sample=True, |
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min_length=50, |
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max_length=768, |
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top_k=30, |
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top_p=0.7, |
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temperature=0.9, |
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repetition_penalty=2.0, |
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num_return_sequences=3) |
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``` |
