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