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/8 - Fine-tuned open-source model to compete with Frontier in price prediction/15 -Day 2 - Comparing LLMs GPT-4 vs LLAMA 3.1 in Parameter-Efficient Tuning.ja_JP.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/15 -Day 2 - Comparing LLMs GPT-4 vs LLAMA 3.1 in Parameter-Efficient Tuning.en_US.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/15 -Day 2 - Comparing LLMs GPT-4 vs LLAMA 3.1 in Parameter-Efficient Tuning.mp4

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/19 -Day 3 - Setting Up the Training Process for Fine-Tuning.ja_JP.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/19 -Day 3 - Setting Up the Training Process for Fine-Tuning.en_US.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/4 -Day 1 - Optimizing LLMs R, Alpha, and Target Modules in QLoRA Fine-Tuning.ja_JP.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/8 -Day 1 - Exploring PEFT Models The Role of LoRA Adapters in LLM Fine-Tuning.ja_JP.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/21 -Day 3 - Fine-Tuning LLMs Launching the Training Process with QLoRA.ja_JP.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/12 -Day 2 - Exploring Tokenizers Comparing LLAMA, QWEN, and Other LLM Models.ja_JP.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/14 -Day 2 - Quantization Impact on LLMs Analyzing Performance Metrics and Errors.ja_JP.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/17 -Day 3 - Understanding Epochs and Batch Sizes in Model Training.ja_JP.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/23 -Day 4 - Keeping Training Costs Low Efficient Fine-Tuning Strategies.ja_JP.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/24 -Day 4 - Efficient Fine-Tuning Using Smaller Datasets for QLoRA Training.ja_JP.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/18 -Day 3 - Learning Rate, Gradient Accumulation, and Optimizers Explained.ja_JP.vtt

/8 - Fine-tuned open-source model to compete with Frontier in price prediction/32 -Day 5 - Revisiting the Podium Comparing Model Performance Metrics.ja_JP.vtt

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