Star History Weekly
#25 ⚖️ Giskard: Open-Source Evaluation & Testing for LLMs and ML models
Read the full article2y agoen
You might also wanna read
A Journey from AI to LLMs and MCP - 3 - Boosting LLM Performance – Fine-Tuning, Prompt Engineering, and RAG
## Free Resources - **[Free Apache Iceberg Course](
datalakehousehub.com·1y ago
Tokasaurus: An LLM Inference Engine for High-Throughput Workloads
Article URL: Comments URL: Points: 14 # Comments: 0
scalingintelligence.stanford.edu·1y ago
A Journey from AI to LLMs and MCP - 2 - How LLMs Work – Embeddings, Vectors, and Context Windows
## Free Resources - **[Free Apache Iceberg Course](
datalakehousehub.com·1y ago
LLM correctness and consistency
Covers techniques like RAG to improve model reliability. — latency, cost, performance
OpenAI Developer Community·11mo ago
LLM correctness and consistency
Covers techniques like RAG to improve model reliability. — latency, cost, performance
platform.openai.com·11mo ago
History-LLMs Project: Developing Large Language Models for Historical Analysis with Ranke-4B Release
Information hub for our project training the largest possible historical LLMs. - DGoettlich/history-llms
github.com·6mo agoA Journey from AI to LLMs and MCP - 3 - Boosting LLM Performance – Fine-Tuning, Prompt Engineering, and RAG
> **Cross-posted.** This article's canonical home is [Data Lakehouse Hub]( ## Free Res...
iceberglakehouse.com·1y ago
Comments
Sign in to join the conversation.
No comments yet. Be the first.