Did I get this result on Grok because I was using the Fun Mode? "Create an image of an olympic athlete crossing pole vaulting over the Eifel tower."
PROMPT ENGINEERING
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Why “fine-tuning” is a misleading term for LLM updates
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“Fine-tuning” is an unfortunate term. FT makes “fine” updates to model weights, but these can effect radical changes in almost any aspect of LLM behavior — to a user it’s more like “retraining.” This makes any use of FT’s lay definition (“tweaking”) in AI contexts confusing.
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Improve LLM Application Accuracy with New Short Course
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Learn a development pattern to systematically improve the accuracy and reliability of LLM applications in our new short course, Improving Accuracy of LLM Applications, built in partnership with @LaminiAI and @Meta, and taught by Lamini’s CEO @realSharonZhou, and Meta’s Senior… pic.twitter.com/b3YogwxPle
— Andrew Ng (@AndrewYNg) 14 août 2024Learn a development pattern to systematically improve the accuracy and reliability of LLM applications in our new short course, Improving Accuracy of LLM Applications, built in partnership with @LaminiAI and @Meta
, and taught by Lamini’s CEO @realSharonZhou
, and Meta’s Senior -
Prompt Caching Reduces Latency by 85% on Long Prompts
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With prompt caching, you can reuse a book's worth of context across multiple API requests. This can also reduce latency by up to 85% on long prompts. Use cases include coding assistants, large document processing, and agentic tool use. Get started: https://
docs.anthropic.com/en/docs/build-
with-claude/prompt-caching
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Claude Prompt Caching Reduces Costs Up to 90%
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Prompt caching with Claude. Caching lets you instantly fine-tune model responses with longer and more instructive prompts—all while reducing costs by up to 90%. Available in beta on the Anthropic API today.
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Get started with ChatGPT prompts for online business
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Want to build a business online? Use these ChatGPT business prompts to get started: https://
godofprompt.ai/blog/chatgpt-p
rompts-for-small-businesses
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LongWriter: Enabling 10,000+ Word Generation from Long Context LLMs
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LongWriter
— AK (@_akhaliq) 14 août 2024
Unleashing 10,000+ Word Generation from Long Context LLMs
discuss: https://t.co/UeebckjbtH
Current long context large language models (LLMs) can process inputs up to 100,000 tokens, yet struggle to generate outputs exceeding even a modest length of 2,000 words.… pic.twitter.com/uXzdZsG4RVLongWriter Unleashing 10,000+ Word Generation from Long Context LLMs discuss: https://
huggingface.co/papers/2408.07
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… Current long context large language models (LLMs) can process inputs up to 100,000 tokens, yet struggle to generate outputs exceeding even a modest length of 2,000 words. -
Image Quality Improvement at 3500 Token Threshold
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En mi caso fue así. Pero el salto a decente noté que fue sobre los 3500. De repente todas mis imágenes salía bien la cara, pero eso sí, los prompts con estilos de ilustración se convirtieron en fotos.
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Overfitting in Pixar Character Image Generation Model
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Para que entendáis a qué me refiero con que el modelo está sobreentrenado. Le estoy pidiendo una imagen de mi hecho personaje de pixar, y oye, de los últimos intentos hay resultados que cumplen…
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Fine-tuning Flux LoRA: Overtraining Effects on Model Rigidity
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Si nos movemos a estilos menos realistas ahí a Flux le cuesta más. Creo que he sobrentrenado al modelo (4000 steps) y por eso cuesta mucho sacarle del realismo Mientras escribo, estoy entrenando un nuevo Lora con menos steps, que creo será menos rígido. Aún así, ni tan mal!