rwkv.cpp
minigpt4.cpp
| rwkv.cpp | minigpt4.cpp | |
|---|---|---|
| 12 | 2 | |
| 1,113 | 546 | |
| 2.8% | - | |
| 6.8 | 6.3 | |
| about 1 month ago | 10 months ago | |
| C++ | C++ | |
| MIT License | MIT License |
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rwkv.cpp
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Eagle 7B: Soaring past Transformers
There's https://github.com/saharNooby/rwkv.cpp, which related-ish[0] to ggml/llama.cpp
[0]: https://github.com/ggerganov/llama.cpp/issues/846
- People who've used RWKV, whats your wishlist for it?
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The Eleuther AI Mafia
Quantisation thankfully is applicable to RWKV as much as transformers. Most notably in our RWKV.cpp community project: https://github.com/saharNooby/rwkv.cpp
Tooling/Ecosystem is something that I am actively working on as there is still a gap to transformers level of tooling. But i'm glad that there is a noticeable difference!
And yes! experiments are important, to ensure improvements in the architecture. Even if "Linear Transformers" replaces "Transformers". Alternatives should always be explored, to learn from such trade-offs to the benefit of the ecosystem
(This was lightly covered in the podcast, where I share IMO that we should have more research into text based diffusion networks)
- Tiny models for contextually coherent conversations?
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New model: RWKV-4-Raven-7B-v12-Eng49%-Chn49%-Jpn1%-Other1%-20230530-ctx8192.pth
Q8_0 models: only for https://github.com/saharNooby/rwkv.cpp (fast CPU).
- [R] RWKV: Reinventing RNNs for the Transformer Era
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4096 Context length (and beyond)
There's https://github.com/saharNooby/rwkv.cpp which seems to work, and might be compatible with text-generation-webui.
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The Coming of Local LLMs
Also worth checking out https://github.com/saharNooby/rwkv.cpp which is based on Georgi's library and offers support for the RWKV family of models which are Apache-2.0 licensed.
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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.
- rwkv.cpp: FP16 & INT4 inference on CPU for RWKV language model (r/MachineLearning)
minigpt4.cpp
What are some alternatives?
llama.cpp - LLM inference in C/C++
vit.cpp - Inference Vision Transformer (ViT) in plain C/C++ with ggml
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.
iNeural - A library for creating Artificial Neural Networks, for use in Machine Learning and Deep Learning algorithms.
ChatRWKV - ChatRWKV is like ChatGPT but powered by RWKV (100% RNN) language model, and open source.
tinyengine - [NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory
mpt-30B-inference - Run inference on MPT-30B using CPU
flashlight - A C++ standalone library for machine learning
verbaflow - Neural Language Model for Go
clip.cpp - CLIP inference in plain C/C++ with no extra dependencies
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
Data-Structures-and-Algorithms - Data Structures and Algorithms implemented In Python, C, C++, Java or any other languages. Aimed to help strengthen the concepts of DSA. Give a Star 🌟 if it helps you.