Fine-tuning technology graph
How Fine-tuning connects to the rest of the AI stack. Click a node to move through the graph, or open the technology page for detail.
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Relationship types
- technical
- alternative
- integration
- evolution
- application
- classification
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Uses and depends on
- Instruction Tuning technique Techniques Instruction Tuning based on Fine-tuning High ✓ source
- Supervised Fine-Tuning technique Techniques Supervised Fine-Tuning based on Fine-tuning High ✓ source
Applied to
- Axolotl framework Frameworks Axolotl used for Fine-tuning High ✓ source
- DeepSpeed framework Frameworks DeepSpeed used for Fine-tuning High ✓ source
- Dropout technique Techniques Dropout used for Fine-tuning High ✓ source
- Gradient Descent technique Algorithms Gradient Descent used for Fine-tuning High ✓ source
- Learning Rate concept Algorithms Learning Rate used for Fine-tuning High ✓ source
- LoRA technique Techniques LoRA used for Fine-tuning High ✓ source
- MLflow tool MLOps MLflow used for Fine-tuning High ✓ source
- PEFT library LLM Frameworks PEFT used for Fine-tuning High ✓ source
- RLHF technique Techniques RLHF used for Fine-tuning High ✓ source
- Regularization concept Algorithms Regularization used for Fine-tuning High ✓ source
- Reinforcement Learning concept Algorithms Reinforcement Learning used for Fine-tuning High ✓ source
- Synthetic Data technique Techniques Synthetic Data used for Fine-tuning High ✓ source
- TRL library LLM Frameworks TRL used for Fine-tuning High ✓ source
- Weights & Biases tool MLOps Weights & Biases used for Fine-tuning High ✓ source
Alternatives
- RAG technique Techniques RAG alternative to Fine-tuning Medium ✓ source
Classification
- Overfitting concept Algorithms Overfitting part of Fine-tuning High ✓ source