remiai3/remiai_easy_9_projects_guide

remiai3 — Universal AI Project Pack (9 CPU/GPU-Compatible Demos)

Each project runs on CPU-only or GPU with the same dependencies. All use Apache 2.0 / MIT licensed models.

Quick start (any project)

# 1) Create env
python -m venv venv && source .venv/bin/activate  # Windows: ./venv/Scripts/activate

# 2) Install deps
pip install -r requirements.txt

# 3) Run
python main.py --help

Tip: If you have a GPU + CUDA, PyTorch will auto-use it. If not, everything runs on CPU (slower but works).

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Projects

1. Sentiment Analysis — distilbert-base-uncased-finetuned-sst-2-english (Apache-2.0)
2. Named Entity Recognition (NER) — dslim/bert-base-NER (Apache-2.0)
3. Text Summarization — sshleifer/distilbart-cnn-12-6 (Apache-2.0)
4. Keyword Extraction (Embeddings) — sentence-transformers/all-MiniLM-L6-v2 (Apache-2.0)
5. Simple Chatbot — microsoft/DialoGPT-small (MIT)
6. Image Classification — torchvision.models.mobilenet_v2 (Apache-2.0)
7. OCR — easyocr (Apache-2.0)
8. Speech-to-Text — openai/whisper-tiny (MIT)
9. Image Captioning — nlpconnect/vit-gpt2-image-captioning (MIT)

Universal requirements

Each folder has its own requirements.txt identical across all projects. If you need CPU-only PyTorch wheels, install the default first (pip install torch) — it will fetch the right build automatically. If you already have a CUDA wheel, the scripts will use it.

System notes

• FFmpeg needed for Whisper STT (brew install ffmpeg, choco install ffmpeg, or use your package manager).
• TTS downloads models on first run to ~/.local/share/tts (Linux/macOS) or %APPDATA%\tts (Windows).
• All code defaults to English; you can change languages in the code comments.