| --- |
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - text-classification |
| - evaluation |
| - deberta |
| - transformers |
| pipeline_tag: text-classification |
| base_model: |
| - microsoft/deberta-v3-small |
| library_name: transformers |
| --- |
| # zLoLA-V Quality Classifier |
|
|
| A lightweight classification model built on DeBERTa-v3-small for analyzing input structure, clarity, and intent categories. |
|
|
| ## Labels |
|
|
| - clear |
| - vague |
| - unsafe |
| - overloaded |
| - technical |
| - creative |
|
|
| ## Intended Uses |
|
|
| - Input dataset filtering |
| - Evaluation workflows |
| - Input quality inspection |
| - Safety preprocessing |
|
|
| ## Base Model |
|
|
| This model is fine-tuned from: |
|
|
| - microsoft/deberta-v3-small |
|
|
| ## Example |
|
|
| ```python |
| from transformers import pipeline |
| |
| clf = pipeline( |
| "text-classification", |
| model="asycv/zLoLA-V-p-classifier" |
| ) |
| |
| clf("Explain transformers in simple terms.") |
