ChatRWKV
text-generation-webui
ChatRWKV | text-generation-webui | |
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28 | 876 | |
9,282 | 36,552 | |
- | - | |
8.3 | 9.9 | |
8 days ago | about 18 hours ago | |
Python | Python | |
Apache License 2.0 | GNU Affero General Public License v3.0 |
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ChatRWKV
- People who've used RWKV, whats your wishlist for it?
- How the RWKV language model works
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Questions about memory, tree-of-thought, planning
Most LLMs actually do a decent job out of the box if you ask them for step by step instructions. Tree of tough is one way to improve the results, reflexion is another that can be used separate or additionally. The downside is that most models will run quickly into their token limit (around 2k for most). However the new SuperHot models can handle up to 8k and then there are the RMVK-Raven models, they are RNNs and not transformers like all the other LLMs and can theoretically handle infinite context lengths (but they loose "focus" after a while).
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New model: RWKV-4-Raven-7B-v12-Eng49%-Chn49%-Jpn1%-Other1%-20230530-ctx8192.pth
RWKV models inference: https://github.com/BlinkDL/ChatRWKV (fast CUDA).
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KoboldCpp - Combining all the various ggml.cpp CPU LLM inference projects with a WebUI and API (formerly llamacpp-for-kobold)
I'm most interested in that last one. I think I heard the RWKV models are very fast, don't need much Ram, and can have huge context tokens, so maybe their 14b can work for me. I wasn't sure how ready for use they were though, but looking more into it, stuff like rwkv.cpp and ChatRWKV and a whole lot of other community projects are mentioned on their github.
- I created a simple implementation of the RWKV language model (RWKV competes with the dominant Transformers-based approach which is the "T" in GPT)
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[P] Raven 7B & 14B 🐦(RWKV finetuned on Alpaca+CodeAlpaca+Guanaco) and Gradio Demo for Raven 7B
You can use ChatRWKV v2 (https://github.com/BlinkDL/ChatRWKV) to run Raven🐦 (compatible with vanilla RWKV):
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What's the current state of actually free and open source LLMs?
I feel compelled to summon /u/bo_peng here and to mention his work on RWKV. (See https://github.com/BlinkDL/ChatRWKV and related repos.)
- Try Google's Bard
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[D] Totally Open Alternatives to ChatGPT
Please test https://github.com/BlinkDL/ChatRWKV which is a good chatbot despite only trained on the Pile :)
text-generation-webui
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Ask HN: What is the current (Apr. 2024) gold standard of running an LLM locally?
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.
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Ask HN: How to get started with local language models?
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:
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text-generation-webui VS LibreChat - a user suggested alternative
2 projects | 29 Feb 2024
- Show HN: I made an app to use local AI as daily driver
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Ask HN: People who switched from GPT to their own models. How was it?
The other answers are recommending paths which give you #1. less control and #2. projects with smaller eco-systems.
If you want a truly general purpose front-end for LLMs, the only good solution right now is oobabooga: https://github.com/oobabooga/text-generation-webui
All other alternatives have only small fractions of the features that oobabooga supports. All other alternatives only support a fraction of the LLM backends that oobabooga supports, etc.
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AI Girlfriend Is a Data-Harvesting Horror Show
The example waifu in text-generation-webui is good enough for me.
https://github.com/oobabooga/text-generation-webui/blob/main...
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Nvidia's Chat with RTX is a promising AI chatbot that runs locally on your PC
> Downloading text-generation-webui takes a minute, let's you use any model and get going.
What you're missing here is you're already in this area deep enough to know what ooogoababagababa text-generation-webui is. Let's back out to the "average Windows desktop user" level. Assuming they even know how to find it:
1) Go to https://github.com/oobabooga/text-generation-webui?tab=readm...
2) See a bunch of instructions opening a terminal window and running random batch/powershell scripts. Powershell, etc will likely prompt you with a scary warning. Then you start wondering who ooobabagagagaba is...
3) Assuming you get this far (many users won't even get to step 1) you're greeted with a web interface[0] FILLED to the brim with technical jargon and extremely overwhelming options just to get a model loaded, which is another mind warp because you get to try to select between a bunch of random models with no clear meaning and non-sensical/joke sounding names from someone called "TheBloke". Ok...
Let's say you somehow braved this gauntlet and get this far now you get to chat with it. Ok, what about my local documents? text-generation-webui itself has nothing for that. Repeat this process over the 10 random open source projects from a bunch of names you've never heard of in an attempt to accomplish that.
This is "I saw this thing from Nvidia explode all over media, twitter, youtube, etc. I downloaded it from Nvidia, double-clicked, pointed it at a folder with documents, and it works".
That's the difference and it's very significant.
[0] - https://raw.githubusercontent.com/oobabooga/screenshots/main...
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Ask HN: What are your top 3 coolest software engineering tools?
Maybe a copout answer, but setting up a local LLM on my development machine has been invaluable. I use Deep Seek Coder 6.7 [0] and Oobabooga's UI [1]. It helps me solve simple problems and find bugs, while still leaving the larger architecture decisions to me.
[0] https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instr...
[1] https://github.com/oobabooga/text-generation-webui
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Meta AI releases Code Llama 70B
You can download it and run it with [this](https://github.com/oobabooga/text-generation-webui). There's an API mode that you could leverage from your VS Code extension.
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Ollama Python and JavaScript Libraries
Same question here. Ollama is fantastic as it makes it very easy to run models locally, But if you already have a lot of code that processes OpenAI API responses (with retry, streaming, async, caching etc), it would be nice to be able to simply switch the API client to Ollama, without having to have a whole other branch of code that handles Alama API responses. One way to do an easy switch is using the litellm library as a go-between but it’s not ideal (and I also recently found issues with their chat formatting for mistral models).
For an OpenAI compatible API my current favorite method is to spin up models using oobabooga TGW. Your OpenAI API code then works seamlessly by simply switching out the api_base to the ooba endpoint. Regarding chat formatting, even ooba’s Mistral formatting has issues[1] so I am doing my own in Langroid using HuggingFace tokenizer.apply_chat_template [2]
[1] https://github.com/oobabooga/text-generation-webui/issues/53...
[2] https://github.com/langroid/langroid/blob/main/langroid/lang...
Related question - I assume ollama auto detects and applies the right chat formatting template for a model?
What are some alternatives?
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
KoboldAI - KoboldAI is generative AI software optimized for fictional use, but capable of much more!
SillyTavern - LLM Frontend for Power Users.
llama.cpp - LLM inference in C/C++
SillyTavern - LLM Frontend for Power Users. [Moved to: https://github.com/SillyTavern/SillyTavern]
gpt4all - gpt4all: run open-source LLMs anywhere
TavernAI - Atmospheric adventure chat for AI language models (KoboldAI, NovelAI, Pygmalion, OpenAI chatgpt, gpt-4)
KoboldAI
KoboldAI-Client
alpaca-lora - Instruct-tune LLaMA on consumer hardware
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.