💡OpenJev and SemIf Trick for LLM Token Probabilities
LLM API trick for token probabilities and webcam frames
TL;DR
OpenJev and SemIf introduce a trick for LLM token probabilities, allowing for quick, single-token generation and webcam frame analysis. Works with vision models, capturing 1 frame per second with Gemma 4 12B on RTX 3090.
OpenJev and SemIf have introduced a trick for reading an LLM's token probabilities, allowing developers to generate single tokens quickly and analyze webcam frames. This trick works with both text and vision models, capturing frames at 1 FPS with Gemma 4 12B on an RTX 3090 and 0.2 FPS with OpenAI's gpt-6-luna. Developers can use this to optimize their workflows, avoiding lengthy answers and costly separate connections. The trick involves writing prompts with state and questions, adding JSON request parameters, and processing the API's log probabilities.
Key Points
OpenJev and SemIf trick allows single-token generation from LLMs, avoiding lengthy answers.
Works with vision models, capturing 1 frame per second with Gemma 4 12B on RTX 3090.
Captures 0.2 frames per second with OpenAI's gpt-6-luna, demonstrating flexibility.
Uses OpenCV to access webcam, captures frames, and sends base64 JPEGs to API.
Includes JSON request format with attachments field for images in local experiments.
Why It Matters
If you're working with LLMs and need to optimize for quick responses or analyze visual data, this trick can save time and reduce costs. It works with both text and vision models, capturing frames at 1 FPS with Gemma 4 12B on an RTX 3090 and 0.2 FPS with OpenAI's gpt-6-luna. Teams using OpenCV and the OpenAI API can leverage this to improve their workflows.
Comments
Be the first to comment
Enjoyed this article?
Get it daily. 7am. Free. Reads in 5 minutes.
Join 3,567 builders reading daily.