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from dataclasses import dataclass
import yt_dlp
import librosa
import xml.etree.ElementTree as ET
import asyncio
from typing import List, Optional, Dict, Any
import httpx
import logging
import subprocess
import os

indiejoseph

分析以下幾篇文章內容，以分析員角度分析，歸納成一份學術性文章。

- 畀出主題、主體同概念
- 必須用廣東話書寫
- 為主體人物或概念提供簡介
- 為主題作總結

文章內容：

# 香港電影業新聞與動態

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import queue
import time
import threading
from transformers.generation.logits_process import (
    TopPLogitsWarper,
    RepetitionPenaltyLogitsProcessor,
)

@torch.inference_mode()
    def inference_v2(

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version: "3.9"
services:
  app:
    image: heartexlabs/label-studio:latest
    restart: unless-stopped
    depends_on:
      - db
    expose:
      - "8080"
    environment:

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$ conda activate ml
(ml) $ conda install ipykernel
(ml) $ ipython kernel install --user --name=<any_name_for_kernel>
(ml) $ conda deactivate

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import torchaudio

def eval(audio, text):
    # convert audio to 16000 sample rate
    audio = torchaudio.transforms.Resample(orig_freq=44100, new_freq=16000)(torch.tensor(audio).unsqueeze(0)).squeeze()
    # process text
    tokenized_seq = torch.tensor([processor.tokenizer(text, add_special_tokens=True).input_ids]).to(device)
    decoder_input_ids = tokenized_seq[:, 1:]
    decoder_input_ids_right_shifted = tokenized_seq[:, :-1]
    # process audio

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const resampling = (audioBuffer: AudioBuffer, targetSampleRate: number): Promise<AudioBuffer> => {
  const offlineAudioContext = new OfflineAudioContext(1, audioBuffer.length, targetSampleRate);

  const source = offlineAudioContext.createBufferSource();
  source.buffer = audioBuffer;

  source.connect(offlineAudioContext.destination);
  source.start();

  return offlineAudioContext.startRendering();

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You are asked to come up with a set of 20 diverse and detailed roleplay scenarios. These scenarios will be given to a large language model and we will evaluate the large language model for completing the roleplay effectively.

Here are the requirements:

1. Ensure the roles and scenarios are diverse, covering different contexts, professions, and situations.
2. The language used for the scenarios should also be diverse. For example, include both formal and informal dialogues.
3. The type of scenarios should be diverse. Include diverse types of interactions like customer service, medical consultations, casual conversations, educational settings, etc.
4. A large language model should be able to complete the roleplay. For example, do not include scenarios that require real-time actions or physical interactions.
5. The scenarios and dialogues should be in **Cantonese**.
6. Each scenario should be detailed, providing a clear context and background. Include relevant information such as the setting, characters involv

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adb -e shell date $(date +%m%d%H%M%Y.%S)