Good question! I am collecting human data on how quantization affects outputs. See here for more information: ggml-org/llama.cpp#5962
In the meantime, use the largest that fully fits in your GPU. If you can comfortably fit Q4_K_S, try using a model with more parameters.
See the wiki upstream: https://github.com/ggerganov/llama.cpp/wiki/Feature-matrix
Researched by Robert Quattlebaum [email protected].
Last updated 2020-02-03.
This document was originally written several years ago. At the time I was working as an execution core verification engineer at Arm. The following points are coloured heavily by working in and around the execution cores of various processors. Apply a pinch of salt; points contain varying degrees of opinion.
It is still my opinion that RISC-V could be much better designed; though I will also say that if I was building a 32 or 64-bit CPU today I'd likely implement the architecture to benefit from the existing tooling.
Mostly based upon the RISC-V ISA spec v2.0. Some updates have been made for v2.2
The RISC-V ISA has pursued minimalism to a fault. There is a large emphasis on minimizing instruction count, normalizing encoding, etc. This pursuit of minimalism has resulted in false orthogonalities (such as reusing the same instruction for branches, calls and returns) and a requirement for superfluous instructions which impacts code density both in terms of size and
| import sympy | |
| def custom_latex_printer(exp, **options): | |
| from google.colab.output._publish import javascript | |
| url = "https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.3/latest.js?config=default" | |
| javascript(url=url) | |
| return sympy.printing.latex(exp, **options) | |
| sympy.init_printing(use_latex="mathjax", latex_printer=custom_latex_printer) |
You can locally pull data from your Rainforest Eagle-200 using cURL.
Rainforest has published a local API document which explains the details of the protocol. But this particular document is about quickly getting to the point and giving you some cURL commands you can use to immediately start pulling out data.
First, I'll assume that you have the following environment variables set:
| #!/usr/bin/env bash | |
| # --slave /usr/bin/$1 $1 /usr/bin/$1-\${version} \\ | |
| function register_clang_version { | |
| local version=$1 | |
| local priority=$2 | |
| update-alternatives \ | |
| --install /usr/bin/llvm-config llvm-config /usr/bin/llvm-config-${version} ${priority} \ |
| ;;;; This script can be loaded during emacs initialization to automatically | |
| ;;;; send `kill-region' and `kill-ring-save' regions to your system clipboard. | |
| ;;;; The OSC 52 terminal escape sequence is used to transfer the selection from | |
| ;;;; emacs to the host terminal. | |
| ;;;; It is based off of the osc52.el copyright the Chromium OS authors, but | |
| ;;;; was modified to add support for tmux, graphical displays, and | |
| ;;;; multi-byte strings. | |
| ;;;; It works in hterm, xterm, and other terminal emulators which support the |
| """ | |
| ldr.py | |
| Display analog data from Arduino using Python (matplotlib) | |
| Author: Mahesh Venkitachalam | |
| Website: electronut.in | |
| """ | |
| import sys, serial, argparse |
In general, check the crt/host_config.h file to find out which versions are supported.
Sometimes it is possible to hack the requirements there to get some newer versions working, too :)
Thrust version can be found in $CUDA_ROOT/include/thrust/version.h.
Download Archives: https://developer.nvidia.com/cuda-toolkit-archive
Release notes for CUDA Toolkit (CTK):
This Gist has been moved to https://github.com/lbgists/audio-spectrum-matplotlib.
