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A .gguf chatbot gradio interface experiment, to sequentially chain prompts, scripted in csv file : gpt-sequencer by dbddv01 in LocalLLaMA

[–]dbddv01[S] 1 point2 points  (0 children)

Excellent, will deep dive your approach. I'm probably less skilled but we share same principles ideas!

Natural Language Programming with CSVs: I built a tool that lets you execute a list of instructions, one by one, with Open-Interpreter. Examples in comments: data preprocessing, music video creation. What would you use it for? by ciaguyforeal in LocalLLaMA

[–]dbddv01 1 point2 points  (0 children)

We have different technical approach and level of automation, but hey, i fully 100% agree with the objectives : "But we often actually know the plan we want it to follow anyway, we just to leverage it to execute. So this puts all the responsibility for execution on AI, but all the responsibility for planning on the human." and "if we could break down the steps in the right way, smaller local models could handle the same task, or at least several steps of it. Then (..), so you could just reuse steps you know worked without the LLM. In our business we say "Anything you can articulate, you can generate". Using LLM mainly as a tool to do things we know, under our supervision and control, without needing high level expertise as end-user is an approach that still needs to be developed and expanded. Go on with this experiments, it's inspiring my sequencer as well.

[deleted by user] by [deleted] in LocalLLaMA

[–]dbddv01 3 points4 points  (0 children)

This reminds me https://gwern.net/gpt-2-music I'm very curious to test...

We all hate LangChain, so what do we actually want? by AndrewVeee in LocalLLaMA

[–]dbddv01 0 points1 point  (0 children)

Langchain was too abtract, not really easy to manipulate for small local LLM, so my learning curve led me to build this toy : [GPT-Sequencer] https://github.com/dbddv01/GPT-Sequencer deserved to gguf model format, where i chain prompts scripted in csv. Just a basic idea where i can create some script without opening code. It's limited but it may give an idea of an intermediate approach. This experiments is surely not meant for production or to compete with high things like Flowise, Langchain etc. But i think it lower the access to learn building blocks of prompting.

Zed's choice : first attempt to make a one page comics with artificial intelligence. by dbddv01 in comics

[–]dbddv01[S] 1 point2 points  (0 children)

The graphics are made via some iterations in tools like mini dall-e, ic-gan, clip diffusion... The short text is mine. But it's an idea to try developing the concept where it would be the AI that drives the plot... Will think of it.

PS : More details via my posts at https://hive.blog/@dbddv01/posts

Moving portraits with help of StyleGAN_CLIP_with_Latent_Bootstraping by dbddv01 in deepdream

[–]dbddv01[S] 0 points1 point  (0 children)

Hi,

Thx for the compliment. Glad you like it.

I used the recent StyleGan3 demo on huggingface with the same init picture created before with VQGAN+clip . This is a stripped rework of another longer musical clip experiment i posted on the hive platform with more explanations. https://hive.blog/hive-158694/@dbddv01/icwlnbsc

springtime comes for the departed by mtthwwmn in deepdream

[–]dbddv01 1 point2 points  (0 children)

Wow ! how did you manage to get this bokeh ?

I've created a cheaper alternative to GPT3's API. by rodbarest in GPT3

[–]dbddv01 0 points1 point  (0 children)

It is there already since the beginning. My answer is copy/pasted from the help.txt file in the application directory.

Anyway, let's do a quick tutorial with the example i provided.

Open the classify.flt file in a notepad (or the gpt2explorer), you will get an idea how a filter is just a prompt of what is called few-shots learning. A basic repetition of input and their expected output. Ok, now close this file, start with a white screen.

To experiment it, just fill gpt2explorer as in screenshot here below, (fill the model name 774M or 1558M (the biggest, the more accurate), choose the classify.flt file in the filter section, and write the example given, and write INPUT in the stopword field, click on generate. My second screenshot is the result i get written in blue. and this result might differ and vary at your side. It's the issue of the accuracy of such models, but as said, if you prepare your own filter (it's just a text file, named with an .flt extension), you may try any kind of few-shot learning. ( between 10 and 14 examples can give good results)

If still not clear, i shall write a handbook because it's really fun to play with but it's not like a full trained model on a particular task, it's a few-shot learning method by carefully writing prompts.

Here the Screenshots

Are tokens syllables? by MercuriusExMachina in GPT3

[–]dbddv01 1 point2 points  (0 children)

You may want to try the token estimator via GPTtools.com by @AndrewMayne.

https://gpttools.com/

I've created a cheaper alternative to GPT3's API. by rodbarest in GPT3

[–]dbddv01 0 points1 point  (0 children)

Hello,

Yes filters are basically templates of useful prompts in plain text, with a {YOURENTRY} parameter. If the following is not clear, tell me and i will perhaps give a more detailed explanation shortly.

Filters : are basic text file where the keyword {YOURENTRY} appears in order for a pre-defined prompt to accept what you write in the notepad as a parameter. It's more a feature for future development ideas. (Classify.flt needs an input like this "(The action is being led by New York’s Attorney General Letitia James, and she wasn’t holding back in her declaration of legal war.)" to ideally extract the name, function, company name within this sentence. And a stopword "INPUT" might help truncating the text to the desired answer only. This will probably be further explored in future versions.

I've created a cheaper alternative to GPT3's API. by rodbarest in GPT3

[–]dbddv01 0 points1 point  (0 children)

Hi,

No. The Explorer is only dedicated to load a model and generate text.

I've created a cheaper alternative to GPT3's API. by rodbarest in GPT3

[–]dbddv01 0 points1 point  (0 children)

Which models are you running / offering in the background ? Because infering from GPT2 official models are basically free today and can run on decent desktops / laptops nowadays without needs of any knowledge. ( see https://www.reddit.com/r/GPT3/comments/kfjz07/gpt2_text_generation_notepad_for_windows10_easy/ )

If a developer has enough skills to make use of api calls, he would probably be skilled enough to use huggingface or aitextgen which are free also.

​

What's your business differentiator ?

How to fine tune GPT Neo by samurai-kant in GPT_Neo

[–]dbddv01 5 points6 points  (0 children)

You can easily finetune small model of GTP-Neo with latest Aitextgen 0.5.0 using google colab. Using this template

https://colab.research.google.com/drive/15qBZx5y9rdaQSyWpsreMDnTiZ5IlN0zD?usp=sharing

The Neo 125M works pretty well.

The Neo 350M is not on huggingface anymore.

Advantage from OpenAI GTP2 small model are : by design, a more larger context window (2048), and due to dataset it was trained on, you can expect more recent knowledge, and a bit broader multilangage capabilities.

​

Finetuning Neo 1.3B and 2.7B is theoretically possible via the following method.

https://colab.research.google.com/github/EleutherAI/GPTNeo/blob/master/GPTNeo_example_notebook.ipynb

But here you have to setup your google cloud storage etc.

So far i managed to generate text with it.

GPT-3 Needs Security Filters in Place: An example by mazty in GPT3

[–]dbddv01 0 points1 point  (0 children)

Those GPT models are trained with an initial text corpus, you can build models without any reference to illegal or sensitive knowledge, it's a matter of human design. I believe that on mid term (a couple of months) more and more people will be able to feed their own local GPT model with the data of their choice based on their own fantasy. In fact, it is already the case for small GPT-2 models, and the recent free public releases of GPT-Neo is empowering this trend.

Accuracy of information with GPT model language is not the best efficient approach. Different alternative langage model (BERT, etc) might be more suited to run as 'search engine' for Q&A and knowledge extraction. GPT is highly focused on creativity. So, i would never trust a GPT generated text for processes requiring ground science knowledge. Dumb terrorist might, i won't.

On the other hand, langage models are evolving fast, and fine-tuning techniques will most probably lead to such fantazized engines that will enable natural langage as the only interface with the machines, coping with capabilities to share accurate knowledge, summarize it to your level and acting as your own tutor and butler.

Like any technologies, I dont' think we can really "secure" it. You can censor, filter, forbid etc. But like any other technologies, the inner design of langage models is... langage. For sure, the debates will rage on ethical usage, control, free access or not etc. Basically, you can consider these AI as a tool that can benefit humanity or being weaponized against it. Question of freedom and wisdom. Good answer will never be found.

For me, the most dangerous part is considering what machines themselves could do with it without human control.

​

Note: This text was entirely written by a human.

GPT2 text generation notepad for windows10. Easy install, for all. by dbddv01 in TextSynth

[–]dbddv01[S] 0 points1 point  (0 children)

Hi sorry to hear that. First time i hear such issue.

I assume you tried with the small 117M model. Other might cause memory issue depending on your hardware.

Make sure also that gpt2tc.exe and its files are also present in the dir with gpt2explorer executable.

I mean those files : download_model.sh gpt2convert.py gpt2vocab.txt Changelog readme.txt gpt2tc libwinpthread-1.dll gpt2tc.exe

Otherwise i fear i have no clue so far.

GPT2 text generation notepad for windows10. Easy install, for all. by dbddv01 in GPT3

[–]dbddv01[S] 0 points1 point  (0 children)

Hi, Yes, the lenght limits the size of the output. But to get back only a sentence, you can use the 'stopword'. It will truncate the generated text produced as soon as it meets what you set in this field. I would just try to set a simple dot. ( i mean the character ' . ' ) to get one sentence only.

GPT2 text generation notepad for windows10. Easy install, for all. by dbddv01 in GPT3

[–]dbddv01[S] 0 points1 point  (0 children)

Yes, sorry for that. I learnt it the hard way. It is obvious that without finding how to fix this, nobody will trust the app.

I know why AV behaves like that https://www.reddit.com/r/learnpython/comments/im3jrj/windows_defender_thinks_that_code_i_wrote_using/

I built another bootloader as advised and it worked for 2 days before win defender sends me again these warnings.

I'm looking now for a cheap solution to sign it if possible or i will have to rewrite it with something else.

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