Possible to share finetuned model with another user?

If I’ve finetuned a model, is it possible to share access to that model with another user through the model id?

Not at this time - it’ll only be accessible to you.

What’s your use case for wanting to share the model? We support teams and organizations, which share the models and billing.

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I could imagine a business case of “FTaaS” (Fine-Tuning as a Service) whereby one company creates and manages finetuning models for clients. But the more I think about this, the less it checks out. One reason is that the company can just sell the custom dataset. Alternatively they can set up an API proxy and markup access to their internally controlled finetuned models… :thinking:


There is definitely some legs to such a dataset marketplace, whether that be commercial or sharing the datasets with other creators. I’m working on how exactly that should look currently - https://finetuning.ai.

Makes sense for someone who has spent time and expertise in compiling a great dataset for a specific purpose to be able to share it with others either for free or for a price.


Yeah, I think that there will be a large demand for bespoke finetuning datasets. For instance, imagine a tech company wants to automate their chat support so they can just give you all their chat logs and you could reconfigure it into a finetuning dataset.


Yes, this is a good idea, and something on our backlog. We were thinking of creating a FT model marketplace, where we allow people to expose their models and they get to profit share, or set a markup.

Sharing datasets is a bit less feasible IMO, and adds a lot of friction for end users, since each model needs to be trained separately, and it’s harder to issue updates.


As @m-a.schenk says, the dataset is indeed where the value is - which is why some vendors might want to protect it as it represents the bulk of their R&D efforts. Selling the dataset would be a one-time transaction (unless the vendor dumps datasets on a regular basis), whereas exposing a model on an FT marketplace would allow for more control over usage and billing.


It will be a tough market because of open source datasets. That’s why I think the most value will actually be in private finetuning services such as for private company data. You would not want to publish a model that had been finetuned with proprietary data.

@daveshapautomator there are a lot of use-cases which open source datasets don’t cover, especially if you want customized behavior that can only be induced by a highly curated dataset. Suppose I have a Q/A-chatbot that was guaranteed (with some probability) to be non-toxic, and there’s a finetuning service that can ‘detox’ my model (ie PALMS). In the case of the PALMS paper, they hired a contract writer to write the prompts and completions for fine-tuning, and chose not to publish the dataset. It would be very convenient in this case, if I can pay a fee to pass my old model through their finetune endpoint, and receive a new model after training. This protects the IP of the vendor, and saves considerable effort on my part.

I am also interested in being able to fine tune a model, and then allow other users to run inferences on it. For example:

curl https://api.openai.com/v1/completions \
  -H "Authorization: Bearer $**SOMEONE_ELSES**_OPENAI_API_KEY" \
  -d '{"prompt": YOUR_PROMPT, "model": **MY**_FINE_TUNED_MODEL}'

I agree with what others have stated about the custom dataset being the primary source of value, aka “business moat” (besides the incredible value provided by GPT-3 itself). Especially for proof-of-concept apps, requiring users to BYOK (bring your own key) is appealing because I don’t have to code up throttling, or a billing wrapper.

I can understand others being hesitant to want this feature for their models. In theory, if your model is fine-tuned well enough, users could take the outputs it generates and quickly create a shadow database of examples that could be used to fine tune a model that closely mirrors your model’s output - benefiting from all the hard work you put into manual data curation.

Perhaps there could be a setting in the OpenAI portal to toggle a fine-tuned model to be public. That way, anyone with a model they don’t want to expose directly to 3rd party callers wouldn’t have to.


@m-a.schenk @jdparsons.dev misuse will definitely be hard to detect, and leakage hard to prevent. This is definitely the case with raw finetuned models, where the user has access to the prompt. If the finetuned model is embedded in an application, however, the model is harder to replicate as there can be additional context in the prompt that is not exposed to the user.


Couldn’t you use Mantium.ai for that?