Can someone answer this - is it possible to train this model ? Like can i feed my own data so that it aligns to my liking
Gpt4all: A chatbot trained on ~800k GPT-3.5-Turbo Generations based on LLaMa
131–140 of 314 posts
Re: Gpt4all: A chatbot trained on ~800k GPT-3.5-Turbo Generations based on LLaMa
#132Earlier quoted context omitted.
This sentence defies lay people: The biggest deal with this isn't the published lora adapter (which seems limited to llama 7b), but the cleaned training data, which is likely better than the previous data sets used to train the alpaca-inspired loras that have been publicly released so far.
A Lora is a layer on top of a model, the big deal isn’t that this exists (it’s a Lora for the weakest llama), but the fact they shared their dataset. The stronger llamas trained with this data will produce even better Lora’s and better results.
Here is a good start in “low-rank adaptation” or LoRA module. A way to train/adapt a general purpose LLM to efficiently and iteratively accommodate specialize data types and knowledge. A bolt-on.
https://arxiv.org/pdf/2106.09685.pdf
Not “on top” but more “in parallel” if I understand correctly
Re: Gpt4all: A chatbot trained on ~800k GPT-3.5-Turbo Generations based on LLaMa
#133Re: Gpt4all: A chatbot trained on ~800k GPT-3.5-Turbo Generations based on LLaMa
#134The real question is what is OpenAI going to do with someone who so clearly flaunted their ToS? If nothing, then OpenAI is going to have a hell of a time making any money out of this for long. But I suspect, that the people who made this are going to get slapped hard with a lawsuit, and essentially forced to shut it down.
Fearmongering plus 2024 elections = Only their LLM stays open commercially maybe? Especially if it helps get Trump elected.
OpenAI’s fear-mongering efforts have been really transparent. As an example, in the ABC News piece, one of their employees discusses asking GPT to help build a bomb. Your employees using words like “bomb” on television is not something that happens by accident.
Re: Gpt4all: A chatbot trained on ~800k GPT-3.5-Turbo Generations based on LLaMa
#135Having spent quite a bit of time playing around with llama.cpp, alpaca.cpp, loras, and the many other llama-based weights lately, here is my impression: The biggest deal with this isn't the published lora adapter (which seems limited to llama 7b), but the cleaned training data, which is likely better than the previous data sets used to train the alpaca-inspired loras that have been publicly released so far. [0] If yo…
I’ll ask a dumb question. On another of the numerous LLM related posts I was asking if any of the self host-able open model can do code summaries at close to the quality of GPT 3.5 turbo. I was basically told nowhere close yet. Can this potentially do that? Ideally I’d like to have it generate descriptions of large amounts of code but would rather not burn tokens and lose privacy via OpenAI api. But I’d gladly keep a…
There is ChatGLM[0], a 6 billion parameter Chinese/English bilingual model that is gaining a reputation as the leading locally runnable LLM for code generation. Maybe look into that. Demo is here[1].
[0]https://github.com/THUDM/ChatGLM-6B/blob/main/README_en.md [1]https://huggingface.co/spaces/multimodalart/ChatGLM-6B
Re: Gpt4all: A chatbot trained on ~800k GPT-3.5-Turbo Generations based on LLaMa
#136What is the best language model that can fit in 1MB or so? I would like to serve it with javascript in a browser...
Re: Gpt4all: A chatbot trained on ~800k GPT-3.5-Turbo Generations based on LLaMa
#137Earlier quoted context omitted.
I’ll ask a dumb question. On another of the numerous LLM related posts I was asking if any of the self host-able open model can do code summaries at close to the quality of GPT 3.5 turbo. I was basically told nowhere close yet. Can this potentially do that? Ideally I’d like to have it generate descriptions of large amounts of code but would rather not burn tokens and lose privacy via OpenAI api. But I’d gladly keep a…
There is ChatGLM[0], a 6 billion parameter Chinese/English bilingual model that is gaining a reputation as the leading locally runnable LLM for code generation. Maybe look into that. Demo is here[1]. [0] https://github.com/THUDM/ChatGLM-6B/blob/main/README_en.md [1] https://huggingface.co/spaces/multimodalart/ChatGLM-6B
I tried this the other day for generating basic Chinese conversations - the quality is surprisingly good. While it's still behind the latest GPT, but the gap isn't as large as I thought it would be.
Re: Gpt4all: A chatbot trained on ~800k GPT-3.5-Turbo Generations based on LLaMa
#138Earlier quoted context omitted.
It's not a secret, in OpenAI api you have to keep sending previous question and responses on top of your new question, essentially you are asking new question but give it more context with the previous questions and answers
Thank you for clarifying this mystery. My mental model of how ChatGPT works is now clearer. I was somehow thinking that in chat mode it would either (a) need to “update state”, or (b) be fed increasingly longer history. I thought (b) would slow down later responses but I guess with their ginormous compute it’s not perceptible to users.
Someone made a version with a buffer which only has a fixed size context history so it stays in constant speed mode. It will only focus on the latest questions.
Re: Gpt4all: A chatbot trained on ~800k GPT-3.5-Turbo Generations based on LLaMa
#139> Reverse a string in python. > In Python, you can reverse a list or tuple by using the reversed() function on it. Here's an example of how to use this method with strings: > my_string = "Hello World" # Define your original string here reversed_str = my_string[::-1] # Use a slice and negative index for reverse order print(reversed_str) Hmm…
Such examples show hilariously the true essence of AR-LLM
Re: Gpt4all: A chatbot trained on ~800k GPT-3.5-Turbo Generations based on LLaMa
#140I had fun using it with a 3090 GPU, it generates responses fairly quickly and can be quite nuanced. I plan to use it a lot more in the coming days, but so far I'm really impressed with how it worked--In my opinion its comparable if not better than Google Bard, but ChatGPT still rules supreme.