Why treating LLMs like simple APIs fails at scale, and how routing, caching, and observability create controlled AI architecture. #finetuningllms
Our First Mistake Was Treating LLMs Like APIs
hackernoon.com
May 12, 2026 at 6:52 PM
Why treating LLMs like simple APIs fails at scale, and how routing, caching, and observability create controlled AI architecture. #finetuningllms
A practical map of LLM post-training: how SFT, reward models, RL (PPO, GRPO), DPO, and RLVR fit together, and why a reward model is not RL. #finetuningllms
How LLMs Are Trained After Pretraining: SFT, Reward Models, and RL Without the Alphabet Soup
hackernoon.com
August 14, 2026 at 3:10 AM
A practical map of LLM post-training: how SFT, reward models, RL (PPO, GRPO), DPO, and RLVR fit together, and why a reward model is not RL. #finetuningllms
December 15, 2025 at 4:23 AM
dvgodoy/FineTuningLLMs: Official repository of my book "A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face" github.com/dvgodoy/Fine...
GitHub - dvgodoy/FineTuningLLMs: Official repository of my book "A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face"
Official repository of my book "A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face" - dvgodoy/FineTuningLLMs
github.com
December 16, 2025 at 2:06 AM
dvgodoy/FineTuningLLMs: Official repository of my book "A Hands-On Guide to Fine-Tuning LLMs with PyTorch and Hugging Face" github.com/dvgodoy/Fine...
Learn the importance of temperature and seed parameters for controlling LLM output randomness. #finetuningllms
The Builder's Dilemma: Balancing Creativity and Consistency in Agentic Workflows
hackernoon.com
March 24, 2026 at 12:20 PM
Learn the importance of temperature and seed parameters for controlling LLM output randomness. #finetuningllms
Learn the difference between fine-tuning a large language model and using Retrieval-Augmented Generation (RAG). #finetuningllms
Fine-Tuning vs RAG – How to Choose the Right Approach to Training LLMs on Your Data
hackernoon.com
July 29, 2025 at 9:52 AM
Learn the difference between fine-tuning a large language model and using Retrieval-Augmented Generation (RAG). #finetuningllms
Fine-tune LLMs with your own data using Apache Answer and InstructLab—no ML team or big infra needed. A practical AI guide for mid-sized teams. #finetuningllms
Fine-Tuning Models with Your Own Data, Effortlessly
hackernoon.com
May 15, 2025 at 3:28 AM
Fine-tune LLMs with your own data using Apache Answer and InstructLab—no ML team or big infra needed. A practical AI guide for mid-sized teams. #finetuningllms