chat-ui VS ComfyUI

Zephyr 141B is a Mixtral 8x22B fine-tune. Here are some interesting details

- Base model: Mixtral 8x22B, 8 experts, 141B total params, 35B activated params

- Fine-tuned with ORPO, a new alignment algorithm with no SFT step (hence much faster than DPO/PPO)

- Trained with 7K open data instances -> high-quality, synthetic, multi-turn

- Apache 2

Everything is open:

- Final Model: https://huggingface.co/HuggingFaceH4/zephyr-orpo-141b-A35b-v...

- Base Model: https://huggingface.co/mistral-community/Mixtral-8x22B-v0.1

- Fine-tune data: https://huggingface.co/datasets/argilla/distilabel-capybara-...

- Recipe/code to train the model: https://huggingface.co/datasets/argilla/distilabel-capybara-...

- Open-source inference engine: https://github.com/huggingface/text-generation-inference

- Open-source UI code https://github.com/huggingface/chat-ui

Have fun!

As long as you have a free Hugging Face account, you can sign up and exploit HuggingChat, a web-based chat interface where you will find 5 large language models to play with (Mixtral-7B-it v0.1 and v0.2, Command R plus, Gemma 1.1-7B-it, Dolphin). You will also have the possibility to exploit several assistants made by the Hugging Face community, or even create your own!

I submitted something about this the other day (and it got flagged)- poked around a little bit and the only interesting thing I could find is this: https://github.com/huggingface/chat-ui/issues/254 and I don't really even understand what it is, it references the stuff the dude who wrote this is discussing. I had kinda written the whole thing off as someone with too much time on their hands and is just f'ing around with stuff for whatever reason.

I think they made this as well: https://chat.openai.com/g/g-KT4gusP3Y-a-l-i-s-t-a-i-r-e-earl... - it doesn't seem very useful.

*¯\_(ツ)_/¯ to me after spending an hr or so poking around, it seemed like a bored modern tech savvy young person playing around.

- https://github.com/huggingface/chat-ui

Hugging Face Chat - open-source repo powering Hugging Chat!

If you don't want to do coding, I think HuggingFace's chat-ui can come in handy with web retrieval RAG and llama-cpp running as a server. Please check their documentation on how to setup( See "Running your own models using a custom endpoint" section on their Github).

yes! it's proprietary, invasive, and harvests your data and use it for improving the AI, Ultman went to Israel weeks after Chatgpt was introduced, Israel like any other tech-giant-country needs to make sure that it has control over that data and/or use it to achieve its goals, so it's better to find offline FOSS alternatives (if you have a decent enough PC) or use HuggingChat as an online FOSS alternative, I find it better than GPT 3.5 in many aspects

I have categorized some of the smartphone brands by their parent company using HuggingChat based on RLHF, Google's Bard, ChatGPT, and Perplexity. All of them are powered by LLMs, and both ChatGPT and Perplexity use GPT-3.5.

I'm looking for something like https://huggingface.co/chat/ or OpenAssistant, but it should target OpenAI's api.

The non standard licensing puts me off in contributing or using this. It is frustrating how the phrase opensource has been diluted in the AI/ML community. ComfyUI has a GPL license [1] while this project uses this [2]. I honestly don't know where I stand since this is a legal document using non-standard phrasing to describe how the rights around the source code.

This is a project that uses a custom license with less rights provided than the ComfyUI project it self-describes as improving. Am not sure the title is reflective of the project.

[1] - https://github.com/comfyanonymous/ComfyUI/blob/master/LICENS...

* LLaVA model: I'll add more documentation. You are right Llava could not generate images. For image generation I don't have immediate plans, but checkout these projects for local image generation.

- https://diffusionbee.com/

- https://github.com/comfyanonymous/ComfyUI

- https://github.com/AUTOMATIC1111/stable-diffusion-webui

Check out ComfyUI for a much more advanced and open source version of this.

https://github.com/comfyanonymous/ComfyUI

I use Stable Diffusion family models for innovative art products.

On a small scale, you have to professionalize ComfyUI’s development. My PR to make it installable and to make a plugin ecosystem that makes sense should not be sitting unmerged (https://github.com/comfyanonymous/ComfyUI/pull/298).

On a medium scale, CLIP is holding you back. I would eagerly buy a 48GB card to accommodate a batch size 1, gradient checkpointed LoRA-trainable model with T5 for conditioning. I want PixArt-a or DeepFloyd/IF with the SDXL dataset and training. I get I can achieve so much with SDXL on 24GB, including just barely a fine tuning, I understand the engineering decisions here, but it’s too weak on prompts.

On a large scale, I’m willing to spend a little money up front. In those conditions you can be far more innovative, you don’t have to make everything for $0. Shane Carruth didn’t make Primer for $0. I’m sure you’ve seen this movie, you get how astoundingly good it is. But he still spent something. He spent only slightly more than an RTX 6000 Ada.

Innovators have budgets. It’s still worth releasing the most powerful possible model for expensive hardware, this is why everyone is talking about Mixtral, but it’s especially true of visual art.

It's litegraph.js [1] and seems to be the only lib they include in /web [2] :

[1] https://github.com/jagenjo/litegraph.js

[2] https://github.com/comfyanonymous/ComfyUI/tree/master/web/li...

It's possibly you might get a later version of Comfy working, but I had no success with this method and the 1st Sept version of Comfy. The older versions are here under Assets... https://github.com/comfyanonymous/ComfyUI/releases

That said, please do learn coding and don't get discouraged when somebody says to learn PyTorch or recommends using a Jupiter notebook with no further information on how to translate the skill into images. I would highly recommend some short term goals. Get your feet wet by taking apart the UIs. The comfy API documentation is here and the A1111 API documentation is here. There is a difference in completeness, welcome to programming. Writing nodes or plugins is also a good way to jump into this world. Custom wildcard logic might be very attractive to you if you aren't the type that want to deal with a nested file structure to simulate logic.

For example ComfyUI can simply be downloaded and run using the portable version (https://github.com/comfyanonymous/ComfyUI/releases/download/latest/ComfyUI_windows_portable_nvidia_cu121_or_cpu.7z) if your not comfortable using GIT etc.

https://github.com/comfyanonymous/ComfyUI scroll down to "Install"