glados-tts VS text-generation-webui

It is being generated using a project called glados-tts (which generates the glados voice from the game Portal): https://github.com/R2D2FISH/glados-tts

I wish that I could tell you. I cloned your repo and running it fails on line 9. Probably missing some dependency that I can not think of. If anybody has an idea please let me know! I got the TTS running by installing from a ready docker package. I do have the GPU power so I'd rather use the HQ version.

total time = 392339.02 ms / 2221 tokens

And my exact command was:

llama-server --model DeepSeek-R1-UD-Q2_K_XL-00001-of-00005.gguf --temp 0.6 -c 9000 --min-p 0.1 --top-k 0 --top-p 1 --timeout 3600 --slot-save-path ~/llama_kv_path --port 8117 -ctk q8_0

(IIRC slot save path argument does absolutely nothing unless and is superfluous, but I have been pasting a similar command around and been too lazy to remove it). -ctk q8_0 reduces memory use a bit for context.

I think my 256gb is right at the limit of spilling a bit into swap, so I'm pushing the limits :)

To explain to anyone not aware of llama-server: it exposes (a somewhat) OpenAI-compatible API and then you can use it with any software that speaks that. llama-server itself also has a UI, but I haven't used it.

I had some SSH tunnels set up to use the server interface with https://github.com/oobabooga/text-generation-webui where I hacked an "OpenAI" client to it (that UI doesn't have it natively). The only reason I use the oobabooga UI is out of habit so I don't recommend this setup to others.

Can't this kind of repetition be dealt with at the decoder level, like for any models? (see DRY decoder for instance: https://github.com/oobabooga/text-generation-webui/pull/5677)

Still nothing better than oobabooga (https://github.com/oobabooga/text-generation-webui) in terms of maximalism/"Pro"/"Prosumer" LLM UI/UX ALA Blender, Photoshop, Final Cut Pro, etc.

Embarrassing and any VCs reading this can contact me to talk about how to fix that. lm-studio is today the closest competition (but not close enough) and Adobe or Microsoft could do it if they fired their current folks which prevent this from happening.

If you're not using Oobabooga, you're likely not playing with the settings on models, and if you're not playing with your models settings, you're hardly even scratching the surface on its total capabilities.

I understand your situation. It sounds super simple to me now but I remember having to spend at least a week trying to get the concepts and figuring out what prerequisite knowledge I would need between a continium of just using chatgpt and learning relevant vector math etc. It is much closer to the chatgpt side fortunately. I don't like ollama per se (because i can't reuse its models due to it compressing them in its own format) but it's still a very good place to start. Any interface that lets you download models as gguf from huggingface will do just fine. Don't be turned off by the roleplaying/waifu sounding frontend names. They are all fine. This is what I mostly prefer: https://github.com/oobabooga/text-generation-webui

Why do people recommend this instead of the much better oobabooga text-gen-webui?

https://github.com/oobabooga/text-generation-webui

It's like you hate settings, features, and access to many backends!

The issue is running the model. Exl2 is part of the ExllamaV2 library, but to run a model, a user needs an API server. The only option out there was using text-generation-webui (TGW), a program that bundled every loader out there into a Gradio webui. Gradio is a common “building-block” UI framework for python development and is often used for AI applications. This setup was good for a while, until it wasn’t.

What I described here is most optimal workflow I found to be working for me. There are multiple ways to run open source models locally worth mentioning like Oobabooga WebUI or LM Studio, however I didn't found them to be so seamless, and fit my workflow.

Some of the tools offer a path to doing tool use (fetching URLs and doing things with them) or RAG (searching your documents). I think Oobabooga https://github.com/oobabooga/text-generation-webui offers the latter through plugins.

Our tool, https://github.com/transformerlab/transformerlab-app also supports the latter (document search) using local llms.

You can use webui https://github.com/oobabooga/text-generation-webui

Once you get a version up and running I make a copy before I update it as several times updates have broken my working version and caused headaches.

a decent explanation of parameters outside of reading archive papers: https://github.com/oobabooga/text-generation-webui/wiki/03-%...

a news ai website: