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Natural Language Processing (NLP) Latest Developments: T0 Model Outperforms GPT3
In case anyone is interested in natural language processing (NLP), I would like to share this here.
It's a more technical discussion.
Since GPT3 was excellent in text generation, the T0 model reaches a new benchmark in terms of performance in various NLP tasks.
Technical Details & Video Explanation
 Paper: https://arxiv.org/abs/2110.08207
 BigScience: https://bigscience.huggingface.co/
 Models on HF hub: https://huggingface.co/bigscience
 Prompt tool: https://github.com/bigscience-workshop/promptsource
These are the Python Package requirements:
1) transformers
2) pytorch
3) sentencepiece
There's an easy way to try out this model with PyTorch & Hugging Face:
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("bigscience/T0pp")
model = AutoModelForSeq2SeqLM.from_pretrained("bigscience/T0pp")
inputs = tokenizer.encode("Is this review positive or negative? Review: this is the best cast iron skillet you will ever buy", return_tensors="pt")
outputs = model.generate(inputs)
print(tokenizer.decode(outputs[0]))
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