wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh -b
~/miniconda3/bin/conda init
source ~/.bashrc
rm Miniconda3-latest-Linux-x86_64.sh
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| #!/usr/bin/env python3 | |
| # -*- coding: utf-8 -*- | |
| """ | |
| End-to-end utility for Groq Whisper: | |
| 1) Silence-based split (ffmpeg silencedetect) | |
| 2) Re-merge adjacent parts under size limit (default 25 MB) | |
| 3) Transcribe each merged audio via Groq Whisper Large v3 | |
| 4) Save per-chunk TXT/JSON and merge into a single TXT | |
| Defaults tuned for your workflow: |
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| // Assets/Editor/HierarchyWebServer.cs | |
| #if UNITY_EDITOR | |
| using System; | |
| using System.Net; | |
| using System.Text; | |
| using System.Threading; | |
| using System.Collections.Generic; | |
| using UnityEditor; | |
| using UnityEngine; |
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| import modal | |
| import os | |
| import io | |
| # Safetensorsモデル (Transformers) を使用するための設定 | |
| MODEL_NAME = "unsloth/Qwen3-VL-8B-Instruct" | |
| # モデルキャッシュ用のVolume | |
| VOLUME_NAME = "qwen3-models-safetensors" | |
| MODEL_CACHE_DIR = "/vol/models" |
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| from PIL import Image | |
| import os | |
| def convert_images_to_pdf(input_png_dir): | |
| # 20枚ごとに画像をグループ化してPDFに変換 | |
| print(input_png_dir) | |
| divide_num = 20 | |
| for group_i in range(0, 220, divide_num): # ここでグループの範囲を設定 | |
| images = [] |
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| import pyautogui | |
| import time | |
| import random | |
| import os | |
| # | |
| # Setting | |
| # | |
| book_dirs = [ |
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