mikecvet/beam
LLM Beam Search Example Implementation
When you need to generate text with large language models, this tool helps you find the most relevant and coherent output. You input a document and a prompt (like "summarize this document"), and it provides a refined text generation that's more accurate and less random than standard model outputs. It's ideal for anyone working with text generation who wants higher quality results.
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Use this if you need more precise and less erratic text generation from an LLM, especially for tasks like summarization or response generation.
Not ideal if you're looking for highly creative, diverse, or unpredictable text outputs where variability is preferred over coherence.
Stars
13
Forks
2
Language
Python
License
MIT
Category
Last pushed
May 03, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/mikecvet/beam"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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