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Originally created by @oliverbob on GitHub (Jan 10, 2024).
Original GitHub issue: https://github.com/ollama/ollama/issues/1889
Steps to reproduce:
Download a new Bible Dataset from KJV Markdown .md
To add more context (for others that might be asking the relationship of this problem with Ollama or dolphin-phi, here's the quick answer:
ollama create kjv -f ./joined.mdollama run kjvAsk questions:
Makes me wonder/question how Phi was developed by microsoft team/community. Trying it on other topics though makes the model extremely accurate.
Question:
Thanks all for creating such a very powerful AI library.
@BruceMacD commented on GitHub (Jan 10, 2024):
Hi @oliverbob, this seems like a good case for fine-tuning or a different model. Before going with the fune-tuning approach I'd encourage you to try
dophin-mixtralor something similar.Addressing your questions:
How do I make the Phi Model obedient to Christian text in a system prompt?
In this case the you're seeing is probably a result of how the model was trained, and not being trained for this specific case.
Must I retrain the model from scratch?
What is the quickest way to retrain this model from a custom dataset?
Training a model from scratch is really difficult, I think what you may be looking for here is fune-tuning. It lets you train new behavior on top of an existing model. Here is a good guide on fine-tuning:
https://brev.dev/blog/fine-tuning-mistral
@easp commented on GitHub (Jan 11, 2024):
What are you actually trying to do? It seems that you are building a markdown file that starts with some excerpts from the bible and concatenating the entire King James Version to it.
What are you doing with it then? Where, exactly does Ollama and phi/dolphin-phi? come into it? I'm going to assume that you are feeding the file to Ollama somehow.
I downloaded the dataset and, knowing that the christian bible is a large book, I tried to put that in terms relevant to use with an LLM.
826,288 words. For our purposes let's say that one word equals one token. The phi-2 and dolphin-phi models in the Ollama library don't specify a context size, so it's using the Ollama default of 2048 tokens. I don't think they work with anything larger than that.
Disobedience? You've crushed a donkey under a pile of rocks and now you are making insinuations about its character.
@oliverbob commented on GitHub (Jan 13, 2024):
Yes, essentially, as you can see, that's what I did to demonstrate the Modelfile creation. The quickest way to talk to a document. For instance,
If you
git clone https://github.com/jmorganca/ollama. If you take ., that would parse all the content of the repo (very impractical), but if you do *.md, it will parse all the docs for you so that you can ask ollama models directly about the repo. But that's just one scenario. Another use case is when you have lots and lots of .pdf, .txt or text only dataset, it is like the quickest way to simulate a fine-tuning mechanism. I like Phi because it smoothly runs on a 4G GPU very fast., I have no success doing that with mistral dolphin-mixtral, mixtral, (or any model greater than orca-mini) since it consumes my GPU resources before I can even ask questions to it.I'm not sure if this is the best way to do it, but since we can make a new model out of a modelfile, but anyways, this was just a test. The thing that I had in mind was to be able to talk to any document.
In this experiment however, I was able to give the model new content but only for as long as the context is NOT the Bible. It is extremely good. Phi create new story lines outside Biblical topics. Anything that you instruct it to do outside the Bible is fine, but if it is any text that are scriptural in nature, (even the entire Bible), it just disobeys.
I was able to do this on large text (not just the Bible) and it works as expected, and I can talk to the document without problems using Ollama Web-UI that's currently attracting a large community. But, keeps me wondering why it won't do it with Biblical text.
Where Ollama comes to the picture is when you do
ollama create kjv -f ./joined.mdfor instance. Sorry if I was not very clear in my presentation, I will add this line into the original question.But like I said, the model is created on top of ollama dolphin-phi. You can talk to the model, but it does not respond to you coming from any text created in that modelfile. I tried it with just the first chapter or smaller modelfile about the Bible and it disobeys.
That's why I'm asking if someone here have problems doing it with any Christian text with success.
@jmorganca commented on GitHub (May 10, 2024):
Hi @oliverbob thanks for the issue. It might be a big hard for the maintainer team to fix this as it's very dependent on the model weights. I'd recommend trying a large set of models including Llama 3 which has much lower false refusal rates than previous models