Large Language Models
15 videos • 501 views • by DataMListic
1
Why Language Models Hallucinate
DataMListic
Download
2
How to Fine-tune Large Language Models Like ChatGPT with Low-Rank Adaptation (LoRA)
DataMListic
Download
3
Multi-Head Attention (MHA), Multi-Query Attention (MQA), Grouped Query Attention (GQA) Explained
DataMListic
Download
4
Transformer Self-Attention Mechanism Explained | Attention Is All You Need
DataMListic
Download
5
LLM Prompt Engineering with Random Sampling: Temperature, Top-k, Top-p
DataMListic
Download
6
Jailbroken: How Does LLM Safety Training Fail? - Paper Explained
DataMListic
Download
7
LLM Tokenizers Explained: BPE Encoding, WordPiece and SentencePiece
DataMListic
Download
8
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits - Paper Explained
DataMListic
Download
9
Chain-of-Verification (COVE) Reduces Hallucination in Large Language Models - Paper Explained
DataMListic
Download
10
RLHF: Training Language Models to Follow Instructions with Human Feedback - Paper Explained
DataMListic
Download
11
BART Explained: Denoising Sequence-to-Sequence Pre-training
DataMListic
Download
12
Sliding Window Attention (Longformer) Explained
DataMListic
Download
13
BLEU Score Explained
DataMListic
Download
14
ROUGE Score Explained
DataMListic
Download
15
Vector Database Search - Hierarchical Navigable Small Worlds (HNSW) Explained
DataMListic
Download