Fine-tuning LLMs
Fine-tune open-source LLMs with LoRA/QLoRA for custom tasks and domain adaptation.
0%
Confidence · no data yet
After this skill you can…
- Prepare fine-tuning datasets
- Run LoRA/QLoRA training with Unsloth or HF Trainer
- Evaluate and merge adapters
- Push models to Hugging Face Hub
Prerequisites
Watch (10 videos)
Fine-tuning T5 LLM for Text Generation: Complete Tutorial w/ free COLAB #coding
→ Fine-tune LLMs for downstream tasks→ Use COLAB for LLM development→ Implement text summarization with LLMs
Train image classifier using transfer learning - Fine-tuning MobileNet with Keras
→ Fine-tune pre-trained models for custom tasks→ Adapt models to new datasets
LLM Fine-tuning: Two Crucial Tips for New Models - LLama 2
→ Fine-tune a LLama 2 model on a custom dataset→ Optimize LLM workflow
Fine-tuning with TensorFlow
→ Fine-tune Transformers models→ Use TensorFlow and Keras for LLMs
MedAI: Vision Language Models & Fine-Tuning (KnowAda)
→ Fine-tune a vision language model using KnowAda→ Mitigate hallucinations in multimodal models
Robust Fine-Tuning of Zero-Shot Models
→ Fine-tune pre-trained models for specific datasets→ Improve in-distribution accuracy
Finetune LLMs on MonsterAPI using Monster Tuner
→ Fine-tune LLMs for specific use-cases→ Improve LLM performance using Monster Tuner
LLM Fine-Tuning 20: OpenAI(GPTs) Fine-Tuning Masterclass | Supervised FT | Token & Cost Analysis
→ Fine-tune OpenAI GPT models→ Estimate token costs for fine-tuning
Flan-T5 Model Fine-tuning: Advanced Techniques for Professionals
→ Fine-tune Flan-T5 models for specific NLP tasks→ Implement task-specific data sets in real-time
NeurIPS Hacker Cup AI: FineTuning
→ Fine-tune large language models with constrained resources→ Optimize memory usage for LLMs
DeepCamp AI