jart

#!/bin/sh
# rename-pictures.sh
# Author: Justine Tunney <jtunney@gmail.com>
# License: Apache 2.0
#
# This shell script can be used to ensure all the images in a folder
# have good descriptive filenames that are written in English. It's
# based on the Mistral 7b and LLaVA v1.5 models.
#
# For example, the following command:

kohya-ss

    def forward(self, x, timesteps=None, context=None, y=None, **kwargs):
        # broadcast timesteps to batch dimension
        timesteps = timesteps.expand(x.shape[0])

        hs = []
        t_emb = get_timestep_embedding(timesteps, self.model_channels)  # , repeat_only=False)
        t_emb = t_emb.to(x.dtype)
        emb = self.time_embed(t_emb)

        assert x.shape[0] == y.shape[0], f"batch size mismatch: {x.shape[0]} != {y.shape[0]}"

Tostino

<#meta#>
- Date: 2023-10-05
- Task: summary
<#system#>
Your main objective is to condense the content of the document into a concise summary, capturing the main points and themes.
<#chat#>
<#user#>
To craft a Final Summary:

1. Read Summarized Sections: Carefully review all the summarized sections of the document. Ensure that you have a clear understanding of the main points, key details, and essential information presented in each section.

Tostino

<#meta#>
- Date: 2023-10-05
- Task: summary
<#system#>
Your main objective is to condense the content of the document into a concise summary, capturing the main points and themes.
<#chat#>
<#user#>
Please read the provided Original section to understand the context and content. Use this understanding to generate a summary of the Original section, incorporating relevant details and maintaining coherence with the Prior Summary.

Notes:

Tostino

<#meta#>
- Date: 2023-10-05
- Task: summary
<#system#>
Your main objective is to condense the content of the document into a concise summary, capturing the main points and themes.
<#chat#>
<#user#>
Please read the provided Original section to understand the context and content. Use this understanding to generate a summary of the Original section. Separate the article into chunks, and sequentially create a summary for each chunk. Focus on summarizing the Original section, ignoring any details about sponsorships/advertisements in the text.

Summarized Sections:

swick

#!/bin/sh

set -euo pipefail
#set -x

MICRODNF_PACKAGES_F38="https://kojipkgs.fedoraproject.org//packages/microdnf/3.9.0/2.fc38/x86_64/microdnf-3.9.0-2.fc38.x86_64.rpm \
                       https://kojipkgs.fedoraproject.org//packages/libpeas/1.34.0/3.fc38/x86_64/libpeas-1.34.0-3.fc38.x86_64.rpm \
                       https://kojipkgs.fedoraproject.org//packages/dnf/4.14.0/2.fc38/noarch/dnf-data-4.14.0-2.fc38.noarch.rpm \
                       https://kojipkgs.fedoraproject.org//packages/libdnf/0.68.0/2.fc38/x86_64/libdnf-0.68.0-2.fc38.x86_64.rpm"

sharadhr

$HOME, Not So Sweet $HOME

• Preface
• 1 What is $HOME to you?
• 2 Setup
  • 2.1 Linux
    • 2.1.1 $HOME
    • 2.1.2 Dot-files and dot-directories
    • 2.1.3 XDG Base Directories
• 2.1.4 xdg-user-dirs

cmcconomy

# DOCUMENTATION NOTE: Regular comments don't print in 'help'; two #'s do.

## +------------------------------------------------------------------------------
## | This Makefile contains targets for various python build / deploy steps.
## |
## | Key Targets to know:

## |      make / make help: Display Help
help:
	@sed -ne '/@sed/!s/## //p' $(MAKEFILE_LIST)

jflam

# To run you'll need some secrets:
# 1. SERPAPI_API_KEY secret in env var - get from https://serpapi.com/
# 2. OPENAI_API_KEY secret in env var - get from https://openai.com

import streamlit as st
import json, os
from langchain.prompts import PromptTemplate
from langchain.llms import OpenAI
from serpapi import GoogleSearch

harubaru

_{masterpiece, best quality, 1girl, green hair, sweater, looking at viewer, upper body, beanie, outdoors, watercolor, night, turtleneck}

Waifu Diffusion 1.4 Anime Release Notes

Download Pages

• HuggingFace Diffusers: https://huggingface.co/hakurei/waifu-diffusion
• Pickled Models: https://huggingface.co/hakurei/waifu-diffusion-v1-4