Research
Free tool I built to score dataset quality (LQS) — feedback welcome [D]
The search results did not return the specific Reddit post content. Based on what was retrieved, I'm unable to produce a fully sourced factual summary of that particular Reddit thread about the LQS...
The search results did not return the specific Reddit post content. Based on what was retrieved, I'm unable to produce a fully sourced factual summary of that particular Reddit thread about the LQS dataset quality scoring tool. Here is what can be responsibly stated from available search context:
A Reddit user in r/MachineLearning shared a free, community-built tool called LQS (likely "Label/LLM Quality Score") designed to automatically evaluate and score the quality of machine learning datasets. The tool aims to give practitioners a quantitative measure of dataset health to guide data curation decisions. The post was tagged as a Discussion [D] thread and actively solicited community feedback to improve the tool.
Note: The Reddit post itself was not directly accessible via search. The summary above is partially inferred from context and the post title. For a fully verified entry, please provide the page content directly or confirm the tool's specific features.
Related
- What image/video training data is hardest to find right now? [R]
- Looking for Feedback & Improvement Ideas[P]
- [[p-pca-before-truncation-makes-non-matryoshka-embeddings-comp|[P] PCA before truncation makes non-Matryoshka embeddings compressible: results on BGE-M3 [P]]]
- [[p-citracer-a-small-cli-tool-to-trace-where-a-concept-comes-f|[P] citracer: a small CLI tool to trace where a concept comes from in a citation graph]]
Source: research