221–230 of 860 posts
If the form is a necktie, the rest of the suit could use some tailoring. It’s far too tall for me to wear.
Earlier quoted context omitted.
It is already on huggingface. Meta never really cared about the download wall.
there is a download wall again :(
https://huggingface.co/localmodels/Llama-2-13B-ggml
Just wait a few minutes for the other variants to be uploaded.
Specifically, can I get this packaged somehow into a thing that I can run on my own server to classify my mail as spam or non-spam? Or at least run it as a service with an API that I can connect to?
I watch the development of those LLMs with fascination, but still wade through tons of spam on a daily basis. This should be a solved problem by now, and it would be, except I don't really want to send all my E-mails to OpenAI through their API. A local model would deal with that problem.
Intersting that they did not use any facebook data for training. Either they are "keeping the gud stuff for ourselves" or the entirety of facebook content is useless garbage.
Hey HN, we've released tools that make it easy to test LLaMa 2 and add it to your own app! Model playground here: https://llama2.ai Hosted chat API here: https://replicate.com/a16z-infra/llama13b-v2-chat If you want to just play with the model, llama2.ai is a very easy way to do it. So far, we’ve found the performance is similar to GPT-3.5 with far fewer parameters, especially for creative tasks and interactions. Dev…
I'm wondering how do people compare different models? I've been trying chatGPT 3.5, bing chat (chatgpt 4 I believe?), and bard, and now this one, and I'm not sure if there's a noticeable difference in terms of "this is better"
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I think TikTok would just use it anyway even if they were denied a license (if they even bothered asking for one). They've never really cared about that kind of stuff.
Anyone who has ever worked in a major social media company knows that this is false - but as another person who has, I will chime in and say this is completely wrong, compliance (especially such obvious compliance) is taken seriously.
Hey HN, we've released tools that make it easy to test LLaMa 2 and add it to your own app! Model playground here: https://llama2.ai Hosted chat API here: https://replicate.com/a16z-infra/llama13b-v2-chat If you want to just play with the model, llama2.ai is a very easy way to do it. So far, we’ve found the performance is similar to GPT-3.5 with far fewer parameters, especially for creative tasks and interactions. Dev…
I'm wondering how do people compare different models? I've been trying chatGPT 3.5, bing chat (chatgpt 4 I believe?), and bard, and now this one, and I'm not sure if there's a noticeable difference in terms of "this is better"
Direct link to request access form: https://ai.meta.com/resources/models-and-libraries/llama-dow...
Direct link to request access on Hugging Face (use the same email): https://huggingface.co/meta-llama/Llama-2-70b-chat-hf
Direct link to repo: https://github.com/facebookresearch/llama
Once you get a link to download on email make sure to copy it without spaces, an option is to open it in a new tab and then download. If you are using fish or another fancy shell, make sure you switch to bash or sh before running download.sh from the repo.
I am not sure exactly how much space is needed but it is likely north of 500GB given that there are two 70B models (you are given the option to download just the small ones in a prompt).
Edit: The_Bloke on HF already has them in GGML format available for download.
https://huggingface.co/TheBloke/Llama-2-7B-GGML https://huggingface.co/TheBloke/Llama-2-13B-GGML
Hey HN, we've released tools that make it easy to test LLaMa 2 and add it to your own app! Model playground here: https://llama2.ai Hosted chat API here: https://replicate.com/a16z-infra/llama13b-v2-chat If you want to just play with the model, llama2.ai is a very easy way to do it. So far, we’ve found the performance is similar to GPT-3.5 with far fewer parameters, especially for creative tasks and interactions. Dev…
Earlier quoted context omitted.
I'm wondering how do people compare different models? I've been trying chatGPT 3.5, bing chat (chatgpt 4 I believe?), and bard, and now this one, and I'm not sure if there's a noticeable difference in terms of "this is better"
Depends on the task. For code, ask it to implement a not-difficult but not-trivial feature. "Please add hooks to the AnkiDroid source code so that addons would be viable" might be a good start, for something that is on my mind. Then compare implementations. For checking hallucinations, ask it about events and trivia that happened eons ago, and also within the last decade. Try some things that it can not possibly know…
Here is a thread exploring differences between llama-v2 vs. gpt3.5: https://twitter.com/rajko_rad/status/1681344850510376960
