LoRA? The parameter-efficient fine-tuning method published 2 years before Llama and already actively used by researchers? RoPE? The position encoding method published 2 years before Llama and already in models such as…
If your starting position is already that Sam Altman lies about everything that doesn't fit your preconceived positions, that doesn't seem like a very useful meaningful position to update.
> Surely if OpenAI had insisted upon the same things that Anthropic had, the government would not have signed this agreement. But they did. "Two of our most important safety principles are prohibitions on domestic mass…
>that they need to rig their elections against themselves to get dissenting voices I don't believe this is true. If you're talking about Non-Constituency Members of Parliament, they are consolation prizes given to best…
My statement was >a (fine-tuned) base Transformer model just trivially blowing everything else out of the water "Attention is All You Need" was a Transformer model trained specifically for translation, blowing all other…
GPT-1 wasn't used as a zero-shot text generator; that wasn't why it was impressive. The way GPT-1 was used was as a base model to be fine-tuned on downstream tasks. It was the first case of a (fine-tuned) base…
Because the author is artifically shrinking the scope of one thing (prompt engineering) to make its replacement look better (context engineering). Never mind that prompt engineering goes back to pure LLMs before ChatGPT…
I believe the above post was highlighting that as a misconception young people may have, not saying it is the case.
Two points to consider, one against and one for. 1) It's a small island, but it's also a major trading port. Which means its whole economy is already geared towards importing food from neighboring countries. 2) On the…
The long story short is you are technically correct but in practice things are a little different. There are 2 factors to consider here: 1. Model Capability You are right that mechanically, input and output tokens in a…
You could easily make the other argument: As a professor of ethics she studies many different ethical systems, including ones that are not mainstream. This means that she can more easily find some ethical system under…
Is it stated somewhere that Radford was inspired by that blog post?
It is no coincidence that EleutherAI named their pretraining dataset "the Pile"
The Pythia models have all the training data, code, and configurations available.
EleutherAI as well.
This arguments feels like it's trying to be an inch too smart. Consider the following: Amazon isn't really an online retail company; it doesn't really sell goods to the consumer. What it does is use "goods" that it…
> the RoPE embeddings in Code Llama were designed for this. The RoPE embeddings were not "designed" for that. The original RoPE was not designed with length extrapolation in mind. Subsequent tweaks to extrapolate RoPE…
BERT was on arXiv before being peer reviewed. As were T5, BART, LLaMA, OPT and GPT-NeoX-20B. The Pile and FLAN were also on arXiv before being peer reviewed. Of course, the original Transformer paper was also on arXiv…
Makes sense! But expensive...
But what would they be calling out? If industry groups want to run a training run based on the configurations of a well-performing model, I don't see anything wrong with that. Now, if they were to claim that what they…
Yep I understood that you were using it informally, just trying to keep things informative for other folks reading too.
I want to jump in and correct your usage of "LLaMA Laws" (even you are using it informally, but I just want to clarify). There is no "LLaMA scaling law". There are a set of LLaMA training configurations. Scaling laws…
If you want a speedrun explanation for how we get to "2": In the limit of model scaling, context size doesn't matter (yes, forget about the quadratic attention), most of the compute is in the linear layers, which boil…
It's actually even less remarkable than that. It was an experiment in having a limited release, to shift the field toward a different release convention. > Nearly a year ago we wrote in the OpenAI Charter: “we expect…
While MoE-LoRAs are exciting in themselves, they are a very different pitch from full on MoEs. If the idea behind MoEs is that you want completely separate layers to handle different parts of the input/computation, then…
LoRA? The parameter-efficient fine-tuning method published 2 years before Llama and already actively used by researchers? RoPE? The position encoding method published 2 years before Llama and already in models such as…
If your starting position is already that Sam Altman lies about everything that doesn't fit your preconceived positions, that doesn't seem like a very useful meaningful position to update.
> Surely if OpenAI had insisted upon the same things that Anthropic had, the government would not have signed this agreement. But they did. "Two of our most important safety principles are prohibitions on domestic mass…
>that they need to rig their elections against themselves to get dissenting voices I don't believe this is true. If you're talking about Non-Constituency Members of Parliament, they are consolation prizes given to best…
My statement was >a (fine-tuned) base Transformer model just trivially blowing everything else out of the water "Attention is All You Need" was a Transformer model trained specifically for translation, blowing all other…
GPT-1 wasn't used as a zero-shot text generator; that wasn't why it was impressive. The way GPT-1 was used was as a base model to be fine-tuned on downstream tasks. It was the first case of a (fine-tuned) base…
Because the author is artifically shrinking the scope of one thing (prompt engineering) to make its replacement look better (context engineering). Never mind that prompt engineering goes back to pure LLMs before ChatGPT…
I believe the above post was highlighting that as a misconception young people may have, not saying it is the case.
Two points to consider, one against and one for. 1) It's a small island, but it's also a major trading port. Which means its whole economy is already geared towards importing food from neighboring countries. 2) On the…
The long story short is you are technically correct but in practice things are a little different. There are 2 factors to consider here: 1. Model Capability You are right that mechanically, input and output tokens in a…
You could easily make the other argument: As a professor of ethics she studies many different ethical systems, including ones that are not mainstream. This means that she can more easily find some ethical system under…
Is it stated somewhere that Radford was inspired by that blog post?
It is no coincidence that EleutherAI named their pretraining dataset "the Pile"
The Pythia models have all the training data, code, and configurations available.
EleutherAI as well.
This arguments feels like it's trying to be an inch too smart. Consider the following: Amazon isn't really an online retail company; it doesn't really sell goods to the consumer. What it does is use "goods" that it…
> the RoPE embeddings in Code Llama were designed for this. The RoPE embeddings were not "designed" for that. The original RoPE was not designed with length extrapolation in mind. Subsequent tweaks to extrapolate RoPE…
BERT was on arXiv before being peer reviewed. As were T5, BART, LLaMA, OPT and GPT-NeoX-20B. The Pile and FLAN were also on arXiv before being peer reviewed. Of course, the original Transformer paper was also on arXiv…
Makes sense! But expensive...
But what would they be calling out? If industry groups want to run a training run based on the configurations of a well-performing model, I don't see anything wrong with that. Now, if they were to claim that what they…
Yep I understood that you were using it informally, just trying to keep things informative for other folks reading too.
I want to jump in and correct your usage of "LLaMA Laws" (even you are using it informally, but I just want to clarify). There is no "LLaMA scaling law". There are a set of LLaMA training configurations. Scaling laws…
If you want a speedrun explanation for how we get to "2": In the limit of model scaling, context size doesn't matter (yes, forget about the quadratic attention), most of the compute is in the linear layers, which boil…
It's actually even less remarkable than that. It was an experiment in having a limited release, to shift the field toward a different release convention. > Nearly a year ago we wrote in the OpenAI Charter: “we expect…
While MoE-LoRAs are exciting in themselves, they are a very different pitch from full on MoEs. If the idea behind MoEs is that you want completely separate layers to handle different parts of the input/computation, then…