lucataco

# Replace /etc/docker/daemon.json docker config in Brev.dev Crusoe GPUs
{
    "default-runtime": "nvidia",
    "mtu": 1500,
    "runtimes": {
        "nvidia": {
            "args": [],
            "path": "nvidia-container-runtime"
        }
    },

lucataco

#!/bin/bash

# This is local cli command that allows users to use kokoro on a Macbook Pro
# Requires you to first run the kokoro docker container:
docker run -p 8880:8880 ghcr.io/remsky/kokoro-fastapi-cpu:latest
# Then save this file to /usr/local/bin
# Finally you can test:
kokoro "The quick brown fox jumped over the lazy dog"
# Or even pipe from a stream like:
llm "tell me a joke" | kokoro

lucataco

# Setup:
# conda create -n wan python=3.10
# conda activate wan
# pip3 install torch torchvision torchaudio
# pip install git+https://github.com/huggingface/diffusers.git@3ee899fa0c0a443db371848a87582b2e2295852d 
# pip install accelerate==1.4.0
# pip install transformers==4.49.0
# pip install ftfy==6.3.1

lucataco

services:
  pihole-unbound:
    image: 'bigbeartechworld/big-bear-pihole-unbound:2024.07.0'
    environment:
      - SERVICE_FQDN_PIHOLE_8080
      - SERVICE_FQDN_PIHOLE_10443
      - 'DNS1=127.0.0.1#5353'
      - DNS2=no
      - TZ=America/Chicago
      - WEBPASSWORD=$SERVICE_PASSWORD_PIHOLE

lucataco

from optimum.quanto import freeze, qfloat8, quantize
from diffusers import FluxPipeline
import torch
import time

seed=1337
generator = torch.Generator("cuda").manual_seed(seed)

pipeline = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16).to("cuda")

lucataco

# conda create -n flux python=3.11
# conda activate flux
# pip install torch==2.3.1
# pip install diffusers==0.30.0 transformers==4.43.3
# pip install sentencepiece==0.2.0 accelerate==0.33.0 protobuf==5.27.3

import torch
from diffusers import  FluxPipeline
import diffusers

lucataco

import torch
import random

random.seed(42)
torch.manual_seed(42)


from transformers import LlamaTokenizer, LlamaForCausalLM
model_path = 'openlm-research/open_llama_3b_v2'
tokenizer = LlamaTokenizer.from_pretrained(model_path, legacy=True);

lucataco

build:
  gpu: true
  python_version: "3.10"
  run:
    - apt update -y && apt install -y software-properties-common python3-launchpadlib && apt update -y && add-apt-repository -y ppa:git-core/ppa && apt update -y
    - apt install -y gcc g++ aria2 git git-lfs wget libgl1 libglib2.0-0 ffmpeg cmake libgtk2.0-0 libopenmpi-dev unzip libssl-dev pkg-config tmux ca-certificates
    - wget https://developer.download.nvidia.com/compute/cuda/12.1.0/local_installers/cuda_12.1.0_530.30.02_linux.run && sh cuda_12.1.0_530.30.02_linux.run --silent --toolkit
    - git clone https://github.com/aristocratos/btop /content/btop && cd /content/btop && make && make install PREFIX=/usr && rm -rf /content/btop
    - pip install notebook pyngrok pickleshare ipywidgets
    - pip install https://github.com/camenduru/wheels/releases/download/replicate/vllm-0.4.0.post1-cp310-cp310-linux_x86_64.whl

lucataco

import os
import cv2
import argparse
import numpy as np

MONITOR_W = 38.5


def write_depth(depth, bits=1, reverse=True):
    depth_min = depth.min()

lucataco

""" To use: install Ollama, clone OpenVoice, run this script in the OpenVoice directory
    brew install portaudio
    brew install git-lfs
    git lfs install

    git clone https://github.com/myshell-ai/OpenVoice
    cd OpenVoice
    git clone https://huggingface.co/myshell-ai/OpenVoice
    cp -r OpenVoice/* .