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In this video I cover the "Multitask Prompted Training Enables Zero-Shot Task Generalization" paper that introduced the T0 transformer.
T0 basically = Google's T5 + LM pretraining + additional training on prompted datasets.
The paper came out of the BigScience workshop.
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✅ Paper: arxiv.org/abs/2110.08207
✅ BigScience: bigscience.huggingface.co/
✅ Models on HF hub: huggingface.co/bigscience
✅ Prompt tool: github.com/bigscience-worksho...
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⌚️ Timetable:
00:00 BigScience workshop, HuggingFace hub
03:00 A high-level overview
04:40 Are we really doing implicit training?
06:30 T0 training and prompt templates
10:55 Choosing the val dataset
13:20 How is T0 trained?
14:55 Results (vs GPT3)
18:25 Ablations (varying prompts and data)
21:30 Discrepancy in GPT3 API vs reported results
22:30 Outro
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Much love! ❤️
Huge thank you to these AI Epiphany patreons:
Eli Mahler
Petar Veličković
Bartłomiej Danek
Zvonimir Sabljic
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💡 The AI Epiphany is a channel dedicated to simplifying the field of AI using creative visualizations and in general, a stronger focus on geometrical and visual intuition, rather than the algebraic and numerical "intuition".
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#t0 #bigscience #huggingface