Ollama & Local LLMs: Fine-Tune, Deploy, Build Python AI Apps By Abdurrahman TEKIN
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Ollama & Local LLMs: Fine-Tune, Deploy, Build Python AI Apps · Program
About this program
Ollama & Local LLMs: Fine-Tune, Deploy, Build Python AI Apps
Online Course
Learning format
Python
Subcategory
English
Course language
$19.99
Price
Price may change · updated within 1–2 weeks
Official program page
What you'll learn in Ollama & Local LLMs: Fine-Tune, Deploy, Build Python AI Apps
- Use Ollama from Python: chat, streaming, generation.
- Build Streamlit UIs on top of local models.
- Add vision: images with multimodal models (e.g. LLaVA-style flows).
- Handle video: frames, Whisper transcription, Q&A over audio.
- Do PDF Q&A and document-grounded prompts.
- Use LangChain: Ollama integration, templates, LLMChain, multi-input prompts.
- Chunk long text and summarize with map-style workflows.
- Use spaCy embeddings: similarity, semantic search, RAG over long text.
- Build note/diary style personal knowledge apps.
- Run CrewAI agents with Ollama (sequential and domain examples).
- Run Hugging Face transformers locally; manage cache and disk use.
- Try TTS and text-to-video scripts where GPU allows.
- Run Unsloth inference (e.g. SmolLM2), inspect tokenizer and model behavior.
- Fine-tune with Unsloth + QLoRA; watch validation for forgetting.
- Test base vs fine-tuned models; merge LoRA adapters.
- Export to Ollama (Modelfile, quantization tradeoffs).
- Capstone: local LLM coding assistant (editor, chat, diffs, run code, shell, optional web research, planning, persistence).
What's Included in Ollama & Local LLMs: Fine-Tune, Deploy, Build Python AI Apps
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