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--- |
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datasets: |
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- SirNeural/flan_v2 |
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metrics: |
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- perplexity |
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tags: |
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- flan |
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- opt |
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- peft |
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--- |
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## FLAN-OPT-6.7b-LoRA |
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OPT was first introduced in [Open Pre-trained Transformer Language Models](https://arxiv.org/abs/2205.01068) and first released in [metaseq's repository](https://github.com/facebookresearch/metaseq) on May 3rd 2022 by Meta AI. |
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This model is [facebook/opt-6.7b](https://hf.co/facebook/opt-6.7b) finetuned with low-rank adapters (https://arxiv.org/abs/2106.09685) on the FLAN datasets (https://arxiv.org/pdf/2210.11416.pdf). |
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Low-rank adapters (r=8) finetuned over 1.6m new tokens of a FLAN task mixture, with the start of each example cut off if it was too large to fit within a 256 token context. |
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The model reaches a train ppl of 4.36 and an eval ppl of 4.32. |
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### Example COT (Chain-of-thought) Prompt: |
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``` |
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Q: Answer the following yes/no question by reasoning step-by-step. Could a dandelion suffer from hepatitis? |
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A: Hepatitis only affects organisms with livers. Dandelions don’t have a liver. The answer is no. |
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Q: Answer the following yes/no question by reasoning step-by-step. Can you write a whole Haiku in a single tweet? |
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A: A haiku is a japanese three-line poem. That is short enough to fit in 280 characters. The answer is yes. |
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Q: Answer the following yes/no question by reasoning step-by-step. Can you reach space with a Cessna? |
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A: |
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``` |
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``` |
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> A Cessna is a small plane. A small plane can't get into space. The answer is no. |
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``` |
