Isn’t this relatively trivial to correct? Just like chain of thought reasoning replaces end tokens with “hmm” to continue the thought can’t users just replace the llm tokens whenever it starts saying “maybe they are…
How do ppl do this if they have a 9-5?
Where is this option? I often get errors about the video being too big and then need to crop my video length to send it. Super annoying
Why are circular saws less prone to injury?
Can you clarify what you mean by using an LLM to “get a list that would even out the numbers”? If you’re doing binary classification, you need datapoints for features as well as the target class so how does an LLM…
It’s kinda easy to check it though. Ask your friends if they use it, preferably non developer. When I find out my accounting friends and marketing friends are using it for basic analytics/promotion write ups I realized…
I’m new to neural nets, when should one use fp8 vs fp16 vs fp32?
It literally says they made 900M off Anthropic in the article
Isn’t this relatively trivial to correct? Just like chain of thought reasoning replaces end tokens with “hmm” to continue the thought can’t users just replace the llm tokens whenever it starts saying “maybe they are…
How do ppl do this if they have a 9-5?
Where is this option? I often get errors about the video being too big and then need to crop my video length to send it. Super annoying
Why are circular saws less prone to injury?
Can you clarify what you mean by using an LLM to “get a list that would even out the numbers”? If you’re doing binary classification, you need datapoints for features as well as the target class so how does an LLM…
It’s kinda easy to check it though. Ask your friends if they use it, preferably non developer. When I find out my accounting friends and marketing friends are using it for basic analytics/promotion write ups I realized…
I’m new to neural nets, when should one use fp8 vs fp16 vs fp32?
It literally says they made 900M off Anthropic in the article