SpikeGPT
ChatRWKV
| SpikeGPT | ChatRWKV | |
|---|---|---|
| 7 | 28 | |
| 693 | 9,301 | |
| - | - | |
| 7.2 | 8.3 | |
| 4 months ago | 3 days ago | |
| Python | Python | |
| BSD 2-clause "Simplified" License | Apache License 2.0 |
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SpikeGPT
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why don't somebody adapt this with pygmalionai ?
it seems to be trainable with a data . GitHub - ridgerchu/SpikeGPT: Implementation of "SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks"
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[D] The Complete Guide to Spiking Neural Networks
The relationship is that SpikeGPT is inspired/is an implementation of RWKV with SNNs.
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[P] New toolchain to train robust spiking NNs for mixed-signal Neuromorphic chips
Have you already seen this? https://github.com/ridgerchu/SpikeGPT
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[R] RWKV 14B ctx8192 is a zero-shot instruction-follower without finetuning, 23 token/s on 3090 after latest optimization (16G VRAM is enough, and you can stream layers to save more VRAM)
Soon :) working on it. Meanwhile take a look at https://github.com/ridgerchu/SpikeGPT which is a SNN version of RWKV, so has some explaination in the paper.
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SpikeGPT: 230M-parameter Spiking Neural Network trained to be a language model
Found relevant code at https://github.com/ridgerchu/SpikeGPT + all code implementations here
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 :)
What are some alternatives?
RWKV-LM - RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
RWKV-LM-LoRA - RWKV is a RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
norse - Deep learning with spiking neural networks (SNNs) in PyTorch.
SillyTavern - LLM Frontend for Power Users.
SillyTavern - LLM Frontend for Power Users. [Moved to: https://github.com/SillyTavern/SillyTavern]
gpt4all - gpt4all: run open-source LLMs anywhere
KoboldAI
alpaca-lora - Instruct-tune LLaMA on consumer hardware
rwkv.cpp - INT4/INT5/INT8 and FP16 inference on CPU for RWKV language model
pygmalion.cpp - C/C++ implementation of PygmalionAI/pygmalion-6b