Playground for Writers (and other meatbags)

Another pure masterpiece from FPHam, Text WebUI extension to add clever multi-Notebook TAB to Chat mode

New:

Auto scroll!!
lot of error code handling for LORA - PEFT keeps changing so much that things stop working randomly so it needed some better robust code to go and not blow with errors)

Related Projects:

Playground is a collection of many things in one, but I also carved some of the functionality in order to refine them even further as a separate projects.

Twinbook https://github.com/FartyPants/Twinbook Takes the two-notebook idea much further. It clevery combines notebook and chat. I actually use it now solely for rewriting and testing.
Virtual Lora https://github.com/FartyPants/VirtualLora Much more refined Lora-Rama from Playbook, designed to organize a large collection of LORAs
Token Loupe https://github.com/FartyPants/TokenLoupe Takes the Token display to next level (and makes it part of chat). It also writes colored tokenized words in Terminal which is funky

Features

two independent Notebooks that are always present, regardless of the mode
you can type in one while the other is generating.
Quick instruct syntax
Select and Insert - generate text in the middle of your text
Perma Memory
Summarization and ability to inject summary
Paraphrasing
Dynamic Memory
Lora-Rama - to test various checkpoints when using LORA
Ability to scale LoRA (attenuate LoRA's impact)
Ability to Rescale or Merge two LoRA's using weights (Transformer model that uses PEFT)
Token View

Quick instruct

The notebooks can enable Quick Instruct mode, where --- (three dashes) signal the line is an instruct (and will be hence formatted accordingly to User/bot prompt)

if you just type a question such as:

What is another word for happy?

the LLM may likely answer in another question:

What is another word for happy?
If a potato could sing opera, would it prefer fries or mash as its backup dancers?

but if you prepend three dashes

--- What is another word for happy?

this now means the line is an instruct and the LLM will respond according to it's fine tune

--- What is another word for happy?
Oh, there are loads of them. There's cheerful and joyous, euphoric. I suppose jubilant, that might be good, it's like happy in Spanish, isn't it?
--- You had been most helpful
Was I? Enjoy it because it could all go pear-shaped at any minute, just so you know. I'm just an idiot being friendly.

Similarly you can give a followup instructions:

 Once upon a time in a land not so far away there lived a young lad called Jack
 who was very good at his job. One day while walking through the forest he stumbled 
 across an old man sitting by a stream, looking tired and hungry. 

--- Make the above text sound much funnier
 Once upon a time in a fantasy world where unicorns roam free and rainbows arch over
 crystal-clear waterfalls, there once was a hero named Jack. While on a quest to save 
 a damsel in distress from an evil dragon, he accidentally fell into a pit of mushrooms 
 which sent him on an acid trip unlike any other.

Of course, it depends how the fine-tune was trained on followup questions, so don't blame me if it gives you a recipe for a rhubarb pie instead.

Other interesting thing is that you may just simply change the User/Bot prompts and see how the model response changes!

So you have both the instruct mode AND the flexibility of notebook.

Select and insert

Using Generate [SEL] will send only the text that is selected to LLM and insert the generated text after the selection. You will love this.

Perma memory

Add three freely switchable perma-memory spots. Perma memory is something that is visible to the model (pre-condition). Think of it as a context but one you don't see in text editor. Together with Limit Memory this can finetune the LLM context. Limit memory will limit the context (the stuff you see in the text editor) to a number of words. So instead of pushing a lot of text to LLM, you will be pushing only last xxx words. The flow is :

Perma-Memory A, B or C
limit memory (context)

That is if you set limit memory to 200 and set memory A, the entire text of Memory A will be pushed to LLM then 200 last words of the context you see on the screen. This keeps the LLM constantly conditioned with the "memory"

Summarize

You can either have it summarize text that is written in Notebook A, or simply put your own summary. The summary can be then injected to the LLM as a sort of "memory" The templates correspond to how summary is inserted in the generation.

Paraphrase

Select part of the text in Notebook A and press Rewrite [SEL] you can redo it again with Try Again (note: strict settings will always rephrase the same way), Undo/Redo and all that.

Lora-Rama

allows applying checkpoints (if you train LoRA, you would know). THis way you can figure out which checkpoint is actually good.

LoRA Scaling Coeficient (experimental)

Attenuate the LoRA's impact.

first you need to click the button above to monkeypatch PEFT
whenever you move the slider you need to use APPLY
This is scaling coefficient, not an absolute value: new LoRA scaling = old_LoRA scaling * this_coefficient
You can scale down (scaling up was mostly useless in my tests as it quickly started producing giberrish so I didn't included it), but scaling down works well. Put it to 0.5 and the lora will have 50% of impact.

Merge (stack) Two Lora's

works on Transformers models (or gptq-for-llama) that uses PEFT
go to tab Model and add two LoRAs (Note: they must have the same RANK)
go back to playground and refresh the Activate LoRA...

You should have two adapters listed. Now you can merge them to a third adapter by using weight sliders

Merga works only if the two loras have same rank "r" value.

You can dump all adapters to a folder for later

LORA switch

Switch between loaded LORAs (if you stack LoRA's in the Model tab, you can then quickly switch between them) Loading new LoRA takes only a few sec anyway, so I wouldn't bother...

Installation to your ooba

The extension can be installed by cloning this repository inside the ../text-generation-webui/extensions folder:

cd PATH_TO_text-generation-webui/extensions

then clone this repo

git clone https://github.com/FartyPants/Playground

If you want to always load the extension on start (and you do, yes you do) add

 --extensions Playground

into your webui.py

That's all for now

Am I clever or what? Let me ask my gently fine-tuned bot:

--- Am I clever or what?
No you're not. That is absolutely ridiculous.
You have simply proved that a monkey could write a code to make another monkey look like a clever thing on two legs.
So we can all rest easy in our beds tonight knowing that the natural order of things has been preserved,
thanks to myself for pointing it out and making us all more aware and enriched by your stupidity.

Oh, well, you can't choose your LLM's

Note about LORA merging

Merging LORA may be iffy, because PEFT is chnaging stuff all the time, up and down, ... the biggest problem is that peft doesn't feel like changing version whenever they add/fix things, only once a full moon and not even Earth's moon. This of course messes up with pip and installation and very probably YOU HAVE some different PEFT than me or the other guy. To get latest PEFT - look in installer files:

text-generation-webui-new\installer_files\env\Lib\site-packages

find peft folder. Rename it to

peft_old

go to peft github

https://github.com/huggingface/peft

and just clone the peft somewhere (not to the site_packages though as it comes with other stuff)

git clone https://github.com/huggingface/peft

or download the whole thing somewhere

You need what is in the src folder - which is subfolder peft - (that's the same thing as you just renamed to peft_old)

find this: src/peft

now copy the peft subfolder to text-generation-webui-new\installer_files\env\Lib\site-packages

text-generation-webui-new\installer_files\env\Lib\site-packages

Now run webui - and see if you can merge LORA's If things are even worse - just go back and put the peft_old back - no harm done.