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May 26 12:28:44 whatnext kernel: Linux version 5.15.0-72-generic (buildd@lcy02-amd64-035) (gcc (Ubuntu 11.3.0-1ubuntu1~22.04.1) 11.3.0, GNU ld (GNU Binutils for Ubuntu) 2.38) #79-Ubuntu SM>
May 26 12:28:44 whatnext kernel: Command line: BOOT_IMAGE=/boot/vmlinuz-5.15.0-72-generic root=UUID=0306af66-cc5a-4dfd-852b-674e234f84aa ro quiet splash vt.handoff=7
May 26 12:28:44 whatnext kernel: KERNEL supported cpus:
May 26 12:28:44 whatnext kernel:   Intel GenuineIntel
May 26 12:28:44 whatnext kernel:   AMD AuthenticAMD
May 26 12:28:44 whatnext kernel:   Hygon HygonGenuine
May 26 12:28:44 whatnext kernel:   Centaur CentaurHauls
May 26 12:28:44 whatnext kernel:   zhaoxin   Shanghai  
May 26 12:28:44 whatnext kernel: x86/fpu: Supporting XSAVE feature 0x001: 'x87 floating point registers'
May 26 12:28:44 whatnext kernel: x86/fpu: Supporting XSAVE feature 0x002: 'SSE registers'

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This worked on 14/May/23. The instructions will probably require updating in the future.

llama is a text prediction model similar to GPT-2, and the version of GPT-3 that has not been fine tuned yet. It is also possible to run fine tuned versions (like alpaca or vicuna with this. I think. Those versions are more focused on answering questions)

Note: I have been told that this does not support multiple GPUs. It can only use a single GPU.

It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.

• Clone llama.cpp from git, I am on commit 08737ef720f0510c7ec2aa84d7f70c691073c35d.

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# ffmpeg -i foo.m4a foo.wav

from pyannote.audio import Pipeline

pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization")
diarization = pipeline("foo.wav")

# RTTM format https://catalog.ldc.upenn.edu/docs/LDC2004T12/RTTM-format-v13.pdf
with open("foo.rttm", "w") as rttm:
    diarization.write_rttm(rttm)

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# Makefile for transregion

CFLAGS = -g
LDFLAGS = -L/usr/X11R6/lib -lXpm -lXext -lX11 -lm

all: transregion

transregion: transregion.o
	$(CC) -o transregion transregion.o $(LDFLAGS)

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/*
 * NOTE: This is a little long because I'm including all XCB setup I have
 * (including handling tiling window managers). It's below the main cairo logic
 * for ease, but included for posterity. This is a subset of a larger program
 * I'm working on.
 *
 * WHAT THIS IS:
 *    A sample program illustrating a problem I'm having with cairo/xcb, where I
 *    want to have a window that supports transparency (alpha channel) for the
 *    background color, and other components, with a regular re-draw cycle

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#!/bin/bash

ngram_count_file="$1"
lm_file="$2"

awk -v f="$ngram_count_file"\
  'function log10(x){ return log(x)/log(10.0) }
   BEGIN {
     while (getline < f) {
       if(/[0-9]+\t[^ ]+$/)             { type[1]++; token[1]=token[1]+$1 }

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#!/usr/bin/python3

################################################################################
##3456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 
##
## Info:
##    python-port of cairo-based countdown effect
##
## Run:
##    chmod +x countdown.py

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#!/usr/bin/env python3
# taken from https://github.com/s-zeid/bin/blob/main/display-transparent
"""Displays an image without a window border or background.
   
   Based on code from http://bit.ly/qfvule
   
"""

import argparse
import os

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while true; do cpulimit  -p $( while true ; do   if [[ ! -z $(pstree  -p -a | awk '/chromium-browser/ && !/awk/' | grep -oP "(?<=sh,).*[0-9]+") ]];  then echo "$(pstree  -p -a | awk '/chromium-browser/ && !/awk/' | grep -oP "(?<=sh,).*[0-9]+")"; break;    fi; sleep 2;    done ) -l 60; done

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#!/usr/bin/env python
# -*- coding: UTF-8 -*-
import math
import re
import pytz
import datetime
from datetime import datetime as dt
from datetime import datetime as dtm, time as datetime_time, timedelta
#from _datetime import *
"""