rwkv.cpp
mpt-30B-inference
| rwkv.cpp | mpt-30B-inference | |
|---|---|---|
| 12 | 3 | |
| 1,111 | 573 | |
| 2.6% | - | |
| 6.8 | 6.2 | |
| 29 days ago | 11 months ago | |
| C++ | Python | |
| 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)
mpt-30B-inference
- New open-source model with 8k context runs on CPU, outperforms GPT-3
- MPT 30B inference code using CPU
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[D] Is there an efficient way to make inferences with open-source LLM?
4-bit. I've used this implementation: https://github.com/abacaj/mpt-30B-inference/tree/main
What are some alternatives?
llama.cpp - LLM inference in C/C++
vllm - A high-throughput and memory-efficient inference and serving engine for LLMs
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.
inference - Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop.
ChatRWKV - ChatRWKV is like ChatGPT but powered by RWKV (100% RNN) language model, and open source.
llm-rp - ✨ Your Custom Offline Role Play with LLM and Stable Diffusion on Mac and Linux (for now) 🧙♂️
verbaflow - Neural Language Model for Go
text-generation-inference - Large Language Model Text Generation Inference
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
chatdocs - Chat with your documents offline using AI.
cformers - SoTA Transformers with C-backend for fast inference on your CPU.