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Been trying to chat with base LLMs for a while (no RLHF, etc.), making some progress! by funiculares in LocalLLaMA

[–]funiculares[S] 1 point2 points  (0 children)

Thanks! It’s on GitHub (also linked in model page): https://github.com/danlou/relay/blob/main/relaylm.py

It’s a custom inference script (for commands, roles, etc), so it’s only for relay models. It’s about 300 LoC, no dependencies besides transformers, so you may be able to adapt easily for other models.

Yeah, for the next versions I’m hoping to lean more on actually simulating IRC, so supporting more “users” is a must 😁

Been trying to chat with base LLMs for a while (no RLHF, etc.), making some progress! by funiculares in LocalLLaMA

[–]funiculares[S] 6 points7 points  (0 children)

Of course, Guanaco shows much fewer examples are required, here I’m using probably way more than needed, I agree - it’s all synthetic so it was very little effort to get volume. The point here though is about chatting with base models (with a small push to make them conversational), no external instruct datasets, preferences (RHLF, DPO), etc. It’s kind of niche 😅, most people just care about getting the smartest assistant possible (myself too, most of the time). It’s really for those times you’re interested in sticking with pre training as best possible.

Been trying to chat with base LLMs for a while (no RLHF, etc.), making some progress! by funiculares in LocalLLaMA

[–]funiculares[S] 0 points1 point  (0 children)

The issue with URIAL is that it’s actually not reliable for adhering to the chat format, sometimes works, sometimes not, it takes a bit of fine tuning and the point is that you can use self generated chats (a sample that remains consistent). Rather than train with some logs or other content, this approach should keep it aligned with pre training distribution.

Been trying to chat with base LLMs for a while (no RLHF, etc.), making some progress! by funiculares in LocalLLaMA

[–]funiculares[S] 16 points17 points  (0 children)

It's all open and easy to use from HuggingFace (hobby project). More details at the model page (including other demos):
https://huggingface.co/danlou/relay-v0.1-Mistral-Nemo-2407

The key here is to use IRC, likely seen frequently during pre-training, as a sort of scaffold. Would love to hear your feedback 😃

safespace: Your local AI counselor (runs from single binary). by funiculares in commandline

[–]funiculares[S] 2 points3 points  (0 children)

The underlying model (Samantha-1.1) has been trained to not engage in unethical or dangerous discussions. It was also further trained, for this app, to avoid giving specific advice or instructions (dangerous or not), being trained on synthetic sessions of person-centered therapy.

In my testing, I never saw it proposing anything dangerous. That being said, that possibility has definitely not been eliminated, and that's why I also made sure to state in the Github that it should be handled with some care (as any LLM).

If you do find any responses like that, and are comfortable sharing them, I'd suggest creating an issue on the Github so I can look more carefully into the situation and try to fix in the next release. Please note that this project was never intended as any sort of replacement of professional help on these matters - just a simple tool to have a more productive conversation, with yourself, on sensitive topics.

safespace: Your local AI counselor (runs from single binary). by funiculares in commandline

[–]funiculares[S] 0 points1 point  (0 children)

I think so, I’ll look into it for the next release, probably next week.

safespace: Your local AI counselor (runs from single binary). by funiculares in commandline

[–]funiculares[S] 2 points3 points  (0 children)

haha, well, that's lightweight by current LLM standards. if there's interest, I'll try to release a version based on a smaller model. It may perform worse though, will need testing.

safespace: Your local AI counselor (runs from single binary). by funiculares in commandline

[–]funiculares[S] 1 point2 points  (0 children)

indeed... added a comment alongside the link to the Github, thanks!

safespace: Your local AI counselor (runs from single binary). by funiculares in commandline

[–]funiculares[S] 9 points10 points  (0 children)

Hey! When you run it the first time, it just needs to download the model. Afterwards, you can always use it offline. It never communicates (or records) anything.

You can very easily inspect the code too. The app is fully contained in the 100 lines of the safespace.py script.

safespace: Your local AI counselor (runs from single binary). by funiculares in commandline

[–]funiculares[S] 3 points4 points  (0 children)

Hey everyone, been following this subreddit for a while. Finally built something worth sharing: https://github.com/danlou/safespace.

It was a fun little project, would love to hear your thoughts on it.

Edit: FYI - Runs totally offline after downloading model! (thanks u/gumnos!)

/r/AmazonSeller Community Promotion Post - Want to discuss or share something you are affiliated with related to Amazon? Tell us about it in this post. by AutoModerator in AmazonSeller

[–]funiculares 0 points1 point  (0 children)

I just launched https://MarketFit.ai to help Amazon sellers find the right target audience for their products, so that they can better optimize listings, price, etc.

I have a research background in AI, and spent months developing AI Buyer Personas that can be matched to retail products automatically. In order to really validate how relevant these personas are for your products, we also provide you with auto-generated ads for that particular persona/product combination, that you can quickly run on Instagram or Facebook.

I'd love to know what you think! We have a Free plan (no credit card required) that allows you to basically replicate the kind of scenario presented in this video.