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palmer is a series of ~1b parameters language models fine-tuned to be used as base models instead of using custom prompts for tasks. This means that it can be further fine-tuned on more data with custom prompts as usual or be used for downstream tasks as any base model you can get. The model has the best of both worlds: some "bias" to act as an assistant, but also the abillity to predict the next-word from its internet knowledge base. It's a 1.1b llama 2 model so you can use it with your favorite tools/frameworks.
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### evaluation
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This model shows exceptional performance and as of now is the best tinyllama-size base model. Furthermore, this proves LIMA paper point and serves as a good open-source alternative to openai's `babbage-002`.
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palmer is a series of ~1b parameters language models fine-tuned to be used as base models instead of using custom prompts for tasks. This means that it can be further fine-tuned on more data with custom prompts as usual or be used for downstream tasks as any base model you can get. The model has the best of both worlds: some "bias" to act as an assistant, but also the abillity to predict the next-word from its internet knowledge base. It's a 1.1b llama 2 model so you can use it with your favorite tools/frameworks.
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### evaluation
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```
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ARC_C HellaSwag PIQA Winogrande Average
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tinyllama-2 | 0.2807 | 0.5463 | 0.7067 | 0.5683 | 0.5255 |
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palmer-001 | 0.2807 | 0.5524 | 0.7106 | 0.5896 | 0.5333 |
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babbage-001 | 0.2944 | 0.5448 | 0.7410 | 0.5935 | 0.5434 |
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deacon-1b | 0.2944 | 0.5727 | 0.7040 | 0.5801 | 0.5434 |
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tinyllama-3 | 0.3029 | 0.5935 | 0.7329 | 0.5959 | 0.5563 |
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tinyllama-2.5 | 0.3191 | 0.5896 | 0.7307 | 0.5872 | 0.5566 |
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palmer-002 | 0.3242 | 0.5956 | 0.7345 | 0.5888 | 0.5607 |
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babbage-002 | 0.3285 | 0.6380 | 0.7606 | 0.6085 | 0.5839 |
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```
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This model shows exceptional performance and as of now is the best tinyllama-size base model. Furthermore, this proves LIMA paper point and serves as a good open-source alternative to openai's `babbage-002`.
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