# Fine tunning with raw data
**URL:** https://community.openai.com/t/fine-tunning-with-raw-data/13896
**Category:** Prompting
**Created:** [December 19, 2021, 6:43am UTC](https://community.openai.com/t/fine-tunning-with-raw-data/13896 "2021-12-19T06:43:44Z")
**Posts on this page:** 4
**Page:** 1
### Author:  [@erwinfeld.work](https://community.openai.com/u/erwinfeld.work)
#### Post date: [December 19, 2021, 6:43am UTC](https://community.openai.com/t/fine-tunning-with-raw-data/13896/1 "2021-12-19T06:43:44Z")
I have a large user manual which I want to use for fine tunning a model
Is it possible to upload the manuel as a whole to the model as “raw” knowledge
and then ad the custom q/a prompts
Or do I need to add every possible answ /question from the doc to the
{“prompt”: “”, “completion”: “”} File ?
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### Author:  [@nunodonato](https://community.openai.com/u/nunodonato)
#### Post date: [December 19, 2021, 9:01am UTC](https://community.openai.com/t/fine-tunning-with-raw-data/13896/3 "2021-12-19T09:01:20Z")
Check the “open-ended” part of the fine-tune documentation
> **[OpenAI API](https://beta.openai.com/docs/guides/fine-tuning/open-ended-generation)**
>
> An API for accessing new AI models developed by OpenAI
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### Author:  [@antonio.ciolino](https://community.openai.com/u/antonio.ciolino)
#### Post date: [December 20, 2021, 12:19am UTC](https://community.openai.com/t/fine-tunning-with-raw-data/13896/4 "2021-12-20T00:19:23Z")
While I don’t generally jump other questions, this one kind of hits on something that I’m struggling with.
I have a small corpus of factual information as a document that I split up into a blank prompt and content in the compression. The competition all ends with the tag END (that might not be great but it’s a start). I also have sentences that are between 500 bytes and 6k. While I suspect that the 6k lines are too long, I don’t think that is my only problem.
In this case I have some facts about a non existent country and it’s laws. So when I inquire in the playground after selecting the fine tune, the responses has the country name, so that is recognized, but one specific thing that I seem to be losing is some context, such as specifics of a law.
I tuned with Currie and Davinci, and while I can ask questions and get responses that return with the specific m country I’ve put in, I don’t think I understand how to return “facts” from the model, in context of open ended generation. So, if I want to all the system to generate a few lines of text for completion, it seems to respond outside of my corpus.
Am I missing the point of the competition endpoint? And I not using the endpoint correctly?
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### Author:  [@EricGT](https://community.openai.com/u/EricGT)
#### Post date: [December 17, 2023, 5:09pm UTC](https://community.openai.com/t/fine-tunning-with-raw-data/13896/5 "2023-12-17T17:09:57Z")