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README.md
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- ARC-AGI
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- ARC
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- code
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---
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This is the second model in the ensemble for the MindsAI @ Tufa Labs team for the ARC Prize 2025 competition. It was originally based on the CodeT5 model from Salesforce. It was modified to have 16 layers in the decoder from the original 24 layers. Testing demonstrated that removing layers was more harmful to performance when removed from the encoder, but was able to fully recover when removing decoder layers.
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- ARC-AGI
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- ARC
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- code
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datasets:
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- WizardLMTeam/WizardLM_evol_instruct_V2_196k
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- Open-Orca/SlimOrca
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- camel-ai/math
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- skeskinen/TinyStories-GPT4
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- rajpurkar/squad_v2
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- garage-bAInd/Open-Platypus
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- Sharathhebbar24/arxiv-math-instruct-50k
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- AlgorithmicResearchGroup/arxiv-physics-instruct-tune-30k
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- TIGER-Lab/MathInstruct
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- neoneye/histogram-comparisons-small-v1
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- ise-uiuc/Magicoder-Evol-Instruct-110K
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- PrimeIntellect/INTELLECT-MATH-SFT-Data
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- PrimeIntellect/verifiable-math-problems
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- sethapun/arithmetic_2md_1to1000
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- EleutherAI/proof-pile-2
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- MMInstruction/M3IT
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- stingning/ultrachat
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- timdettmers/openassistant-guanaco
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- Dahoas/instruct-synthetic-prompt-responses
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- pankajmathur/WizardLM_Orca
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---
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This is the second model in the ensemble for the MindsAI @ Tufa Labs team for the ARC Prize 2025 competition. It was originally based on the CodeT5 model from Salesforce. It was modified to have 16 layers in the decoder from the original 24 layers. Testing demonstrated that removing layers was more harmful to performance when removed from the encoder, but was able to fully recover when removing decoder layers.
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