galahad-classifier-0.6B

TerenceLau/galahad-classifier-0.6B

galahad-classifier-0.6B is a text classification model from TerenceLau. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

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596M

2.4 GB on disk

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Hugging Face

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: qwen3
Access: Public
Created: Nov 29, 2025
Updated: Nov 29, 2025
SHA: 89a7c8dc

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Base models

Qwen/Qwen3-Embedding-0.6B

Model card

From the Hugging Face model README

Galahad-Quality-Classifier

Galahad

Model Type: Sequence Classification Model
Base Model: Qwen/Qwen3-Embedding-0.6B

This is a text classification model designed to enable qualitative data annotation, facilitate the creation of quality-specific data blends, and allow for the addition of metadata tags based on document quality. (Unlike nvidia's quality-classifier, this is a Domain-specific classifier)

The model classifies documents (e.g., text samples, comments, reviews, or web pages) into one of three distinct quality classes:

Class ID	Class Name	Score Mapping	Quality Description
2	High Quality	Score > 4	Highly informative, professional, and well-structured content.
1	Medium Quality	3 ≤ Score ≤ 4	Acceptable, non-offensive, and relevant content with moderate structure.
0	Low Quality	Score < 3	Poorly structured, potentially spammy, low-information, or inappropriate content.

The score is labeled by prompting the Deepseek-V3.2(Chat) via official api.

Results

For 300M version:

Label	Precision	Recall	F1-Score	Support
0	0.81	0.66	0.73	119
1	0.78	0.84	0.81	354
2	0.42	0.39	0.41	69
Accuracy	—	—	0.75	542
Macro Avg	0.67	0.63	0.65	542
Weighted Avg	0.74	0.75	0.74	542

For 0.6B model:

Label	Precision	Recall	F1-Score	Support
0	0.75	0.72	0.74	119
1	0.81	0.81	0.81	354
2	0.47	0.52	0.49	69
Accuracy	—	—	0.75	542
Macro Avg	0.68	0.68	0.68	542
Weighted Avg	0.76	0.75	0.75	542

Limitations: The quality assessment is inherently subjective as the data is labeled by a single model and may vary among different models. The dataset is relatively small with the size is only 30k.

Task: Text Classification
Library: transformers
Type: qwen3
License: mit
Created: Nov 29, 2025
Updated: Nov 29, 2025