luiscape

import sys
import time

import zmq
from common import Message, app

from server import process_message


def zmq_query(address: str, n_messages: int = 10):

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#!/usr/bin/env bash
# Needed in order to support the ollama/ollama image.
exec "$@"

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# ## Basic setup
from __future__ import annotations

import io
import os
import time
from pathlib import Path

import modal

luiscape

"""
Script to run batch inference using HuggingFace's zero-shot text-classification model on Modal.

Based on the tutorial: https://modal.com/docs/guide/ex/batch_inference_using_huggingface 

Goal: filter a large Hugging Face dataset for food-related images (based on the text caption).
"""
import io

import modal

luiscape

"""
Script to run batch inference using HuggingFace's zero-shot text-classification model on Modal.

Based on the tutorial: https://modal.com/docs/guide/ex/batch_inference_using_huggingface 

Goal: filter a large Hugging Face dataset for food-related images (based on the text caption).
"""
import io

import modal

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# Runs diffusers-rs on Modal.
import os
import time
import modal
import subprocess

CARGO_PATH:str = "/root/.cargo/bin/cargo"


def _convert_clip():

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import io
import os
import time
from pathlib import Path

import modal
import typer

stub = modal.Stub("stable-diffusion-cli")
app = typer.Typer()

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import io
import time
import modal
import os
import torch
import diffusers

from pathlib import Path

stub = modal.Stub("local-model-mount-test")

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"""This script downloads all neural networks used in the HuggingFace `diffuser`'s
`StableDiffusionPipeline` pipeline. This also downloads the parameters from the scheduler
`EulerAncestralDiscreteScheduler` because that is a fast and effective scheduler.

This requires the env var `HUGGINGFACE_TOKEN` to be populated with a HuggingFace
access token.

The default cache location is: /vol/cache. This can be changed by populating
the environment variable `CACHE_PATH`.

luiscape

#!/bin/bash

#
#  Instally the theme library.
#
pip install jupyterthemes

#
# Configure to use preferred theme.
#