Dive into the world of text embeddings. This course will guide you through leveraging text embeddings to enhance various natural language processing (NLP) tasks.
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Updated
Feb 5, 2024 - Jupyter Notebook
Dive into the world of text embeddings. This course will guide you through leveraging text embeddings to enhance various natural language processing (NLP) tasks.
Boost LLM reliability with dynamic sampling, retry logic, and a lightweight Go‑based proxy.
Latency, diversity, and quality benchmark for autoregressive decoding strategies on RTX 2070: greedy, top-k, top-p, min-p, and beam search across GPT-2 models.
sdkgenai 🛠️🔃📦 : Gen AI SDK # Model Parameters # Safety Filters # Multi-turn Chat # Content Streaming # Asynchronous Requests # Token Counting # Context Caching # Function Calling # Batch Prediction # Text Embeddings
phi3mini 🧊🖥️🛝 : Microsoft Phi 3 Mini Model # Generative AI # Chat Playground # Microsoft Foundry
Charla sobre determinismo y temperatura en modelos de lenguaje (temperature, top-p, top-k, muestreo) + Spec-Driven Development aplicado a productos institucionales. Deck reveal.js con demos interactivas.
Implementation demonstrating how temperature, top-p (nucleus sampling), and top-k sampling parameters transform raw logits into probability distributions for text generation. Includes mathematical explanations and visual examples of each sampling strategy.
Drag temperature, top_k and top_p and watch a real softmax distribution reshape live, with every stage of the truncation pipeline shown and the edge cases explained.
Add a description, image, and links to the top-p topic page so that developers can more easily learn about it.
To associate your repository with the top-p topic, visit your repo's landing page and select "manage topics."