Dino Fancellu fancellu

https://huggingface.co/spaces/Fancellu/Kokoro-TTS-Zero-CPU

To run from docker

docker run -it -p 7860:7860 --platform=linux/amd64 registry.hf.space/fancellu-kokoro-tts-zero-cpu:latest python app.py

https://huggingface.co/spaces/Fancellu/bark-pytorch2.6-compatible

This solves the PyTorch 2.6 breaking change where weights_only=True became the default, causing issues with older model files that contain non-tensor objects, with monkey patch patched_load()

Updated to Python 3.11, latest Gradio, and requirements.txt

If you have a GPU, you can run from Docker Desktop directly

docker run -it -p 7860:7860 --gpus=all --platform=linux/amd64 registry.hf.space/fancellu-bark-pytorch2-6-compatible:latest python app.py

	import gradio as gr
	import numpy as np
	import spaces
	import torch
	import random
	from PIL import Image

	from diffusers import FluxKontextPipeline
	from diffusers.utils import load_image

	import zio._
	import scala.{ Console => SConsole }
	import scala.io.StdIn
	import java.io.{ BufferedReader, IOException }
	import scala.util.Try

	object InterruptableReadLine extends ZIOAppDefault {

	def altReadLine(reader: BufferedReader = SConsole.in) =
	ZIO

	import zio._

	object FakeConsoleExample extends ZIOAppDefault {

	private val program = ZIO.serviceWithZIO[Console] { console =>
	for {
	_ <- console.printLine("Going to the grocery store")
	input <- console.readLine("How are you? ")
	_ <- console.printLine(s"You said: $input")
	} yield ()

	package main

	import (
	"fmt"
	"math/rand"
	"sync"
	"time"
	"unsafe"
	)

	package main

	import (
	"fmt"
	"time"
	)

	func greet(st string, done chan bool) {
	fmt.Println(st)
	done <- true

	import cats.effect.{IO, IOApp}
	import fs2.{Stream, text}
	import fs2.io.file.{Files, Path}
	import fs2.io.{stdout, stderr}

	import scala.util.Try

	object WindowedAverage extends IOApp.Simple:

	private object Fahrenheit:

	import scala.annotation.targetName
	import scala.util.boundary
	import scala.util.boundary.{Label, break}

	// Works in Scala 3.4.1

	def firstIndex[T](xs: List[T], p: T): Int = {
	boundary:
	for (x, i) <- xs.zipWithIndex do if (x == p) break(i)
	-1

	package main

	import (
	"fmt"
	"strconv"
	)

	// Maps over collection of T and applies function f to each item
	// Returns a new slice with the transformed items
	func mapf[T any, U any](items []T, f func(T) U) []U {