Look at their limited docs, I feel it's a little simpler than toolformer, probably more like the blenderbot models for search, and prompt engineering.

- Matching intent from the prompt to a description of the plugin service

- extracting relevant terms from the prompts to send as query params based on description of the endpoint

- model incorporates API response into model response

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"The file includes metadata about your plugin (name, logo, etc.), details about authentication required (type of auth, OAuth URLs, etc.), and an OpenAPI spec for the endpoints you want to expose.The model will see the OpenAPI description fields, which can be used to provide a natural language description for the different fields.We suggest exposing only 1-2 endpoints in the beginning with a minimum number of parameters to minimize the length of the text. The plugin description, API requests, and API responses are all inserted into the conversation with ChatGPT. This counts against the context limit of the model." - https://platform.openai.com/docs/plugins/introduction

I expect it's more likely that people will run their own chatbots with proprietary content. (Even if just built on top of the GPT API)

For example you might have a news chatbot that knows the news and has up-to-date information not available to ChatGPT. And you'd pay a monthly subscription to the news company for it, not to OpenAI.

Unless you plan on quantizing your model or loading it layer by layer, I'm afraid 2B parameters is the most you'll get. 10GB VRAM is not really enough for CV nowadays, let alone NLP. With quantization, you can barely run the 7B model.

4 bit doesn't matter at the end of the day since it's not supported out of the box, unless you intend to implement it yourself.

Why does LlaMa 7B (pure) perform so MUCH better than Alpaca 30B (4bit)?

There was an amazing image creator model published today. I don't remember the name. Please help. :(

Also, to avoid this in the future, could someone let a brother know which outlets should I follow to stay ahead of the news?

Sparse Widget Iso-Flop Transformations (Tailored). SWIFT-Tailored 🎶🎵🧑‍🎤

Good point, that baking in could also include the overall sense of how to get the syntax right

If it fails, reply that it screwed up and needs to fix it. I bet that would work.

Is this a bug in google scholar https://scholar.google.com/citations?view_op=view_citation&hl=en&user=TDk_NfkAAAAJ&citation_for_view=TDk_NfkAAAAJ:vRqMK49ujn8C

Many of tiles by Joseph Redmon seem to be some random title https://scholar.google.com/citations?view_op=view_citation&hl=en&user=TDk_NfkAAAAJ&citation_for_view=TDk_NfkAAAAJ:mvPsJ3kp5DgC

I suspect future versions will do both. They will "bake in" some basic APIs like simple calculator, calendar, fact look ups. They will use in context for 3rd party APIs.

Sure, my next paper will introduce Transformers, a new method for distillation of neural network models.

GPT is really good at outputting json. Just tell it you want the output in json, and give an example.

So far in my testing, it's got a success rate of 100%, although I'm sure it may fail occasionally.

1. This massively increases the utility of ChatGPT. You can have it order food. You can have it query your data without paying for fine-tuning.

2. This smooths over some of the base models' shortcomings. It can now call Wolfram for computations. It can lookup facts instead of making them up.

“Plan a vacation for me and book it” (Expedia plug-in)

So If I had a pdf, I could use faiss to make am it into an embedding, and then llama / alpaca to use the pdf as a base for a chatbot ?

Initially just a chat bot to test how strong it it

But ultimately use it to help me code up websites

I'm at work so I don't have the prompt handy, but I instructed chat GPT to output commands in the following format:

[deviceName:state]

So chatGPT might reply with:

> I turned on your bedroom light [bedroom light:on] and turned up the temperature [thermostat:72]

All you have to do is parse the messages for [:] and trigger the thing.

EDIT:

I told it to place all commands at the end, but it insists on inlining them. Easy enough to deal with.

NotOpenAI will have to figure out a way for people to make money from the process though. Expedia can get traffic from it, but why would a content website feed its data to the bot? It's not getting any ad revenue from traffic .

Prompt. Thanks. Damn auto correct needs ChatGPT level intelligence.

I didn’t hook up voice because of that awkward part. If I could get my hands on a raspberry pi I might make my own listening device.

Isn't this what Neeva should be doing with our phones?

To me the browser plugin is the only one you need. Wolfram Alpha is a website, Instacart is a website, everything is a website. Just have it use the website, done. Plugins seem like a way to get people excited about giving the AI permission to use their stuff, but it's not technically necessary.

This news made me want to learn Python.

I think ChatGPT plugings offers OpenAI a platform, which I think will compete very soon with Apple’s appstore. I think developers will like the possibility of grabbing a huge market once the appstore is running. I add here ablog post, whereI list the process of registering you plugin: https://tmmtt.medium.com/chatgpt-plugins-8f174eb3be38

With memory offloading and 8-bit quantization you may be able to run the 13B model, but slowly. The 7B will be faster.