llama-mps
llama
| llama-mps | llama | |
|---|---|---|
| 4 | 1 | |
| 83 | 189 | |
| - | - | |
| 3.8 | 2.8 | |
| 9 months ago | about 1 year ago | |
| Python | Python | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 only |
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llama-mps
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llama.cpp now officially supports GPU acceleration.
There are currently at least 3 ways to run llama on m1 with GPU acceleration. - mlc-llm (pre-built, only 1 model has been ported) - tinygrad (very memory efficient, not that easy to integrate into other projects) - llama-mps (original llama codebase + llama adapter support)
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LLaMA-7B in Pure C++ with full Apple Silicon support
There is also a gpu-acelerated fork of the original repo
https://github.com/remixer-dec/llama-mps
- Llama-CPU: Fork of Facebooks LLaMa model to run on CPU
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[D] Tutorial: Run LLaMA on 8gb vram on windows (thanks to bitsandbytes 8bit quantization)
I tried to port the llama-cpu version to a gpu-accelerated mps version for macs, it runs, but the outputs are not as good as expected and it often gives "-1" tokens. Any help and contributions on fixing it are welcome!
llama
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LLaMA-7B in Pure C++ with full Apple Silicon support
Repetition penalty is a matter of, generate a token, then multiply that logit by the penalty. (If the logit is negative, divide instead of multiply.)
https://github.com/shawwn/llama has an implementation (check the commit history).
What are some alternatives?
llama - Inference code for Llama models
llama-dl - High-speed download of LLaMA, Facebook's 65B parameter GPT model [UnavailableForLegalReasons - Repository access blocked]
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
amx - Apple AMX Instruction Set
awesome-ml - Curated list of useful LLM / Analytics / Datascience resources
whisper.cpp - Port of OpenAI's Whisper model in C/C++
llama - Inference code for LLaMA models
LLaMA_MPS - Run LLaMA inference on Apple Silicon GPUs.
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ