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 600m llama 2 model (since is 4bit quantized) so you can use it with your favorite tools/frameworks.
evaluation 🧪
note that this is a zero-shot setting as opposite to open llm leaderboard's few-shot evals
This model is as good as tinyllama base while being half the size.
training 🦾
Training took 1.5 rtx 2060 gpu hours. It was trained on 15,000 gpt-4 shuffled samples. palmer was fine-tuned using lower learning rates ensuring it keeps as much general knowledge as possible.
prompt 📝
no prompt 🚀
Note
As of today 1/4/2024 is still not possible to convert to gguf,
see more here
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