LongLLaMA vs Stanford Alpaca
Overview
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Detailed Comparison
It is a model fine-tuned from the LLaMA 7B model on 52K instruction-following demonstrations. It behaves qualitatively similarly to OpenAI’s text-davinci-003, while being surprisingly small and easy/cheap to reproduce. | It is a large language model capable of handling long contexts of 256k tokens or even more. It is built upon the foundation of OpenLLaMA and fine-tuned using the Focused Transformer (FoT) method. |
Instruction-following model;
Fine-tuned from a 7B LLaMA model on 52K instruction-following data
| Capable of handling long contexts;
Based on OpenLLaMA and fine-tuned with the Focused Transformer (FoT) |
Statistics | |
GitHub Stars 30.2K | GitHub Stars 1.5K |
GitHub Forks 4.0K | GitHub Forks 85 |
Stacks 0 | Stacks 0 |
Followers 0 | Followers 1 |
Votes 0 | Votes 0 |
Integrations | |
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