Orca 2: Teaching Small Language Models How to Reason
Orca 2: Teaching Small Language Models How to Reason
At Microsoft, we’re expanding AI capabilities by training small language models to achieve the kind of enhanced reasoning and comprehension typically found only in much larger models.
Orca 2 released by Microsoft!
Full weights here:
https://huggingface.co/microsoft/Orca-2-7b
https://huggingface.co/microsoft/Orca-2-13b
My own exllamav2 quants here:
https://huggingface.co/bartowski/Orca-2-7b-exl2
https://huggingface.co/bartowski/Orca-2-13b-exl2
GGUF from TheBloke (links to GPTQ/AWQ inside it):
What's the context window size?
according to the config it looks like it's only 4096, and they specify in the arxiv that they kept the training data under that value so it must be 4096.. i'm sure people will expand it soon like they have with others
How does it compare to Mistral? That’s the best performing 7b model and it’s suspiciously missing from this report.
I'm looking forward to trying it today, I think this might make a good RAG model based on the orca 2 paper, but testing will be needed