CogView VS DALLE-mtf

This web app, which is mentioned in the CogView (1) GitHub repo, is/was using a "slightly different" model than the CogView2 GitHub repo.

The web app for CogView2 has been available for months, if I am not mistaken. See this GitHub repo for the link.

Is the CogView2 demo avaliable here the same as the CogView2 paper released?

On March 16, 2022, the following was added to the CogView GitHub repo: "News! The demo for a better and faster CogView2 (formal version, March 2022) is available! The lastest model also supports English input, but to translate them into Chinese often could be better."

Yes, CogView 2 is free to use, and is available as a web app here. CogView 2's image description text needs to be in simplified Chinese; an English-to-simplified Chinese icon appears after typing 9 characters. The styles are a quick way to add text snippets to the image description text; I forgot to mention that I used "HD Photography" style for this post.

Github https://github.com/THUDM/CogView

I used the web app for the new version 2 of CogView, then upscaled with a web app version of SwinIR, and then cropped with a paint app. Both of these are free.

This is from the new version of CogView that was released a few weeks ago. There is a link to the new web version about 1/4 of the way down its GitHub page. It is free to use, with no paid option available. Tip: The input needs to be in simplified Chinese. An English-to-simplified Chinese translator icon appears after typing 9 characters.

A method to prevent generating watermark.

GitHub repo for older version of CogView.

This vision is in line with EleutherAI, a non-profit organization founded in July 2020 by a group of researchers. Driven by the perceived opacity and the challenge of reproducibility in AI, their goal was to create leading open-source language models.

My current idea is to utilize the EleutherAI pythia (Databricks Dolly). I would like to know whether translating the Dolly-15k dataset into the desired language using state-of-the-art translation techniques like DeepL would be a viable approach to fine-tune the Pythia base model. I want to use this model for semantic search, so perfection is not a necessity.

There are open source AI efforts, like EleutherAI. Needless to say, they are lagging behind big players, but it's better than nothing.

The new GPT 3.5 isn't aware what are GPT-3.5 or davinci-002 (repeatable) and claimed that it was designed by EleutherAI and has only 6 bil parameters (wasn't been able to repeat but didn't really try).

Hi, my name is Stella Biderman and I run EleutherAI, the one of the foremost non-profit research institutes in the world that trains and studies large language models. I have been involved with the majority of models to hold the title “largest open source GPT model in the world” and have dabbled in exploring using plagiarism detection tools to identify code written by GPT-J.

dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA)

It is true that Emad needs to find an appropriate business model. The good news is that the hype is still undergoing. I'm sure that Emad can grab another round of liquidity injection. He got plenty of resources. Remember he is also from the finance industry. He got https://www.eleuther.ai/ which can supply a secured, in-house custom LLM equivalent to bloombergGPT.

By promoting fully open-source AI, i.e. making datasets, models, methodology and codebases freely available and transparent. What OpenAI claimed to be aiming for, basically.