cformers
alpaca.cpp
| cformers | alpaca.cpp | |
|---|---|---|
| 4 | 94 | |
| 315 | 9,878 | |
| 0.6% | - | |
| 6.7 | 9.4 | |
| 5 months ago | about 1 year ago | |
| C | C | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
cformers
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[P] rwkv.cpp: FP16 & INT4 inference on CPU for RWKV language model
it's a combination of things, and removing python from the loop isn't essential to achieving most of these performance gains. the main trick is quantizing the weights and compiling the model. concrete example that builds on top of ggml with python APIs: https://github.com/NolanoOrg/cformers
- Cformers 🚀 - "Transformers with a C-backend for lightning-fast CPU inference". | Nolano
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FauxPilot – an open-source GitHub Copilot server
We will add quantized CodeGen for fast inference on CPUs up on cformers (https://github.com/NolanoOrg/cformers/) by later today.
alpaca.cpp
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LLaMA Now Goes Faster on CPUs
Where's the 30B-in-6GB claim? ^FGB in your GH link finds [0] which is neither by jart nor by ggerganov but by another user who promptly gets told to look at [1] where Justine denies that claim.
[0] https://github.com/antimatter15/alpaca.cpp/issues/182 -
Is there potential to short NVDA?
You can just download the language model, dude!!! Everyone doesn’t need to make their own and the open source models literally get better every day.
- [Oobabooga] Alpaca.cpp est extrĂŞmement simple Ă travailler.
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Hollywood’s Screenwriters Are Right to Fear AI
Alpaca
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Square Enix’s AI Tech Demo Is a Staggering Failure
Square could have also trained a more specific data source for their NLP, very similar to Alpaca. Alpaca was trained from interactions from a larger dataset. So while it isn't as smart, it's still able to understand instructions and act upon them.
- [Singularity] Ich bin Alpaka 13B - Frag mich alles
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Alpaca Vs. Final Jeopardy
The model I found was in 8 parts. The alpaca.cpp chat client (chat.cpp) needs to be modified to run the 8 part model, documented here: https://github.com/antimatter15/alpaca.cpp/issues/149
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LocalAI: OpenAI compatible API to run LLM models locally on consumer grade hardware!
try the instructions on this github repo https://github.com/antimatter15/alpaca.cpp, its not the best one but I was able to run this model on my linux machine with 16GB memory, I think its a good starting point.
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What educational materials do you think would be most useful during/after collapse?
Doesn't run offline. If you're running something without a beefy-ish GPU, there's https://github.com/antimatter15/alpaca.cpp .
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ChatGPT Reignited My Passion For Coding
Ye, atm. toying with alpaca 7B/13B in a local install.
What are some alternatives?
llama.cpp - LLM inference in C/C++
gpt4all - gpt4all: run open-source LLMs anywhere
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.
CodeGen - CodeGen is a family of open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex.
coral-pi-rest-server - Perform inferencing of tensorflow-lite models on an RPi with acceleration from Coral USB stick
rwkv.cpp - INT4/INT5/INT8 and FP16 inference on CPU for RWKV language model
ggml - Tensor library for machine learning
llm - An ecosystem of Rust libraries for working with large language models
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
gpt4all.cpp - Locally run an Assistant-Tuned Chat-Style LLM
alpaca-lora - Instruct-tune LLaMA on consumer hardware