Sorry for asking but is there an example output and an example input?
You can interact with the full model here: https://talktotransformer.com/
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OpenAI Releases Largest GPT-2 Text Generation Model
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Re: OpenAI Releases Largest GPT-2 Text Generation Model
#112Earlier quoted context omitted.
Hello! Spinning Up author here. I would love to hear your thoughts on this! So far I have had a lot of success teaching people about DDPG using this code example, but I'm grateful for every fresh perspective. :) Feel free to reach out by email, jachiam at openai.
There is no function in the world that should ever take 17 parameters. If the algorithm permits such configuration, as I am sure it does, then it should take a configuration object which has all these values. The object could then be constructed using special purpose factories that take fewer parameters, and then customized from there as needed. It may be an indication that the whole thing needs refactoring though.
You refactor that way but then you make it unnecessarily more complicated.
Re: OpenAI Releases Largest GPT-2 Text Generation Model
#113Re: OpenAI Releases Largest GPT-2 Text Generation Model
#114You can try it at: http://textsynth.org
Here's another one, seed text in italics. Clearly some Star Trek used in the training data.
"Engage", said Captain Picard from the bridge of the Enterprise. "But sir", Commander Data began, "this must have been part of something called the Borg."
"You know I didn't tell them that," said Picard, "I have a very hard time talking to them."
- Picard, Data, and Worf while the ship is under attack by Borg drones at Federation border
"The Borg don't know that they're being infected with something dangerous. And they're not too fond of it. There's a saying: 'Borgs eat Borges. Borges eat Borges.' They'll get tired of eating their own."
Re: OpenAI Releases Largest GPT-2 Text Generation Model
#115Just like various chat bot incarnations, it's reasonably OK at generating generic sentences without real understanding. I tried several attempts with this leading fragment: "Is borrow checking unique to Rust? Probably not. But". The results are not pretty (the best one is as follows). Not impressed at all with this giant model :|
"Is borrow checking unique to Rust? Probably not. But the Rust library is written by and for Rust programmers, so if you're looking for a library that's designed for the language you already know, this might be your first choice.
The library is still in a fairly early stage. It does not support the standard libraries.
If you're interested in reading about how the library works, the docs are up on GitHub for reference!
How can I get this for my project?
Get it here: https://github.com/paulp/rustbinder
I've just read your blog post and want to use it, what can I do?
If you're looking for a project to use this library for, check out the docs for the "RustBinder project".
What are the current limitations and how will future changes affect this library?
This is still a work in progress. The library currently does not support the standard Rust library. There are a few work in progress"
Re: OpenAI Releases Largest GPT-2 Text Generation Model
#116Re: OpenAI Releases Largest GPT-2 Text Generation Model
#117Wow, some samples are frighteningly good. I was impressed by previous models and I don't know if I'm just lucky this time, but... wow. Can anybody who is not into climbing even tell this is all fake? Jain Kim is an experienced climber. In 2006, she became the first woman from Korea to climb all five 8,000 meters (24,064 ft) peaks in the Swiss alpine ski run Alps in 24 hours. In 2009, she made history again by setting…
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Re: OpenAI Releases Largest GPT-2 Text Generation Model
#118Prompt: "Real things don't exist unconditionally and things that exist unconditionally are not real. However the reality has an essense. It is"
Response: "an actual thing, and it is not the thing to which we attach meaning. It is not real because it is not a thing. And therefore, it does not possess the qualities that are inherent in all real things."
Just wow. Sure, there are a few logical mistakes here, but this response serves as a good prompt for my bio-GPT. In other words, we usually need some starting points or hints for analysis and discovering these hints is non trivial because whatever we can think of is not very new to us. This GPT just gave me an answer that smells like a serious wisdom and I'll surely dig in that direction to see if this idea has any substance.
Edit: what's happening here is while I can't ask this model to give me a short and conscise summary on a topic, I can still interrogate this model and find out what it's seen in the training set. I can't possibly read all these books in the training set, but now I can rapidly navigate in the multidimensional meaning space: I tell it where to start and it says what it seems in close proximity to my prompt. This is a breakthru.
Re: OpenAI Releases Largest GPT-2 Text Generation Model
#119Earlier quoted context omitted.
Just an afterthought, but you could probably cobble something together that asks someone for some basic prompts, like names, locations, etc, then uses a series of templates to generate a chapter of text that's reasonably coherent and tailored to an individual.
So. 1. Feed in all the Game of Throne books 2. Generate final book 3. Profit?
You're joking, but I hope we can see this in RPGs of the future.
Re: OpenAI Releases Largest GPT-2 Text Generation Model
#120Earlier quoted context omitted.
The right place for a chill after work beer. Free peanuts, but don’t order “the other” in the name of science. Free peanuts, but don’t order “the other” in the name of science. The last thing you’ll see after work is a sign that says, “Sorry we are closed on Tuesday because we have peanuts.” The last thing you’ll see after work is a sign that says, “Sorry we are closed on Tuesday because we have peanuts.“
This is some Escher level shit. These words, just like his paintings, make sense totally within your window of vision as you move your eyes through, but make no sense on the whole.
I would not be surprised at all to find a paragraph like that in some fiction, especially in poem form.