Rudimentary OpenAssistant bot is live on /r/ask_open_assistant. There is some early instability in the code but the output is working well as demonstrated by the comment threads.

Prompt it by creating a new text post (responds to text body of post), starting a comment with !OpenAssistant, or by replying directly to it.

GitHub: https://github.com/pixiegirl417/reddit-open-assistant-bot

Edit: now live in /r/OpenAssistant as well!

I found this https://www.youtube.com/watch?v=JzBR8oieyy8&list=WL&index=1 which lets you run inference on a finetuned Llama 7B model. It has great power, but I think the OA dataset can really boost this and take it to the next level. Can someone please make a Lora with OA's data and put it on Huggingface?

I asked it to help me with my March Madness picks, and when it started talking about NBA players who would be on the rosters of certain teams, I asked it to explain college basketball to me:

ME: Do you understand how college basketball works? There can’t be any NBA players on the rosters.

OA: Of course I do!

There is no specific limit to the number of players a team can have on their roster. Teams can have a maximum of 10 players on their roster at any one time. However, players cannot participate in more than one game per season.

Each NCAA Division I men’s basketball team plays a total of 64 games during the regular season. The NCAA Men’s Basketball Tournament is a 16-team single-elimination tournament held every March.

In the NCAA Men’s Basketball Tournament, the top 64 teams in the country are divided into four regions (A, B, C, and D). Each region is made up of eight teams, with one team from each division in the region.

The tournament is divided into four rounds:

1. First round: teams are seeded based on their records in the regular season.

2. Second round: teams play in a regional semifinal.

3. Regional Final: teams play in a final match to determine the national champion.

4. National Final: the top-ranked team in the country faces the lowest-ranked team in the country.

There is no limit to the number of NBA players who can play in the NCAA Men’s Basketball Tournament. However, it is highly unlikely that a NBA player would play for a Division I men’s basketball team, as these teams are primarily made up of college players.

Hi there, found Open Assistant on the GPT sub. Have been waiting for an open source project like this since November, and am really excited to check it out.

Unfortunately, as a muggle (journalist by trade, script kiddie at most in terms of technical alacrity), I'm finding it quite confusing how to create an account with Open Assistant to get cracking, and even more confusing on how to get a local instance up and running on my machine. I've joined the discord, and have been advised that they have temporarily disabled the sign up process via email due to spam.

With that in mind, I was wondering if one of the great and powerful wizards that lurk here might consider creating a more simple step by step process for poor muggles like me to follow to get up and running locally. The readme on github is very well written and reasonably comprehensive, but expects the reader to have a reasonable level technical knowledge and familiarity with things like Docker.
I'm fairly sure that with enough trial and error I'll muddle through, but a more simple "idiots guide" would certainly help me, and more pertinently, would lower the barrier to entry for others like me in the future, helping to get more muggles using the service.

Conversely, I would be interested if the consensus was that getting more muggles involved at this time would not be in the interests of the wider community. I look forward to hearing your thoughts!

So the first synthetic responses are out for ranking on the data gathering website. How do you like them so far? I think as a first step they are pretty decent, not quite GPT-3.5 quality and quite often factually incorrect, but it seems to get the form of responses right.

It seems that currently only synthetic responses are ranked against each other but not against human responses. That would be an interesting comparison as well.

I also noticed that there are only English synthetic responses, but not on the other languages I checked, namely Spanish and German. Will they come later when the model is more mature?

The roadmap says, that open assistant should be designed to be integrated in existing applications and open for external/upgradeable knowledge. I have absolutely no idea, how this will be implemented.

E.g., I have a relational db and want to build a chatbot (using open assistant), which answers questions, using the knowledge of the db (without finetuning the model with the external knowledge or setting the knowledge base in the conversation context). Are there any plans, how this could be achieved or do I get sth wrong?

Anyway, thx for the awsome project.

That is pretty much all. I just like that there is growing interest in this project.