๐Ÿง 
Intent Student L6 Uniform Distilled model by gomyk
โญ 38.3
๐Ÿง 
Model

Intent Student L6 Uniform Distilled

by gomyk hf-model--gomyk--intent-student-l6_uniform_distilled
Nexus Index
38.3 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 2
R: Recency 93
Q: Quality 65
Tech Context
Vital Performance
15 DL / 30D
0.0%
Source โ†’
Audited 38.3 FNI Score
Tiny - Params
- Context
15 Downloads
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hf-model--gomyk--intent-student-l6_uniform_distilled
License Apache-2.0
Provider huggingface
๐Ÿ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__gomyk__intent_student_l6_uniform_distilled,
  author = {gomyk},
  title = {Intent Student L6 Uniform Distilled Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/gomyk/intent-student-l6_uniform_distilled}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
gomyk. (2026). Intent Student L6 Uniform Distilled [Model]. Free2AITools. https://huggingface.co/gomyk/intent-student-l6_uniform_distilled

๐Ÿ”ฌTechnical Deep Dive

Full Specifications [+]

Quick Commands

๐Ÿค— HF Download
huggingface-cli download gomyk/intent-student-l6_uniform_distilled
๐Ÿ“ฆ Install Lib
pip install -U transformers

โš–๏ธ Nexus Index V2.0

Methodology Index Protocol
38.3
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 2
Recency (R) 93
Quality (Q) 65

๐Ÿ’ฌ Index Insight

FNI V2.0 for Intent Student L6 Uniform Distilled: Semantic (S:50), Authority (A:0), Popularity (P:2), Recency (R:93), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
---

๐Ÿš€ What's Next?

๐Ÿ“Š

Find Training Datasets

Discover datasets compatible with this model

๐Ÿ“ˆ

Compare Benchmarks

See how this model ranks on standard tests

โšก

Deployment Guide

Understand deployment options

Technical Deep Dive

L6_uniform_distilled (Distilled)

Lightweight multilingual sentence encoder optimized for intent classification. Created from paraphrase-multilingual-MiniLM-L12-v2 via layer pruning + corpus-based vocabulary pruning + knowledge distillation.

Model Details

Property Value
Teacher paraphrase-multilingual-MiniLM-L12-v2
Architecture XLM-RoBERTa (pruned)
Hidden dim 384
Layers 6 / 12
Layer indices [0, 2, 4, 7, 9, 11]
Strategy 6 layers, evenly spaced (general-purpose)
Vocab size ~38,330 (pruned from 250K)
Parameters 26,184,576
Safetensors size 98.1MB
Distilled Yes

Supported Languages (18)

ko, en, ja, zh, es, fr, de, pt, it, ru, ar, hi, th, vi, id, tr, nl, pl

Quick Start

python 
from sentence_transformers import SentenceTransformer

model = SentenceTransformer("L6_uniform_distilled")

sentences = [
    "์˜ˆ์•ฝ ์ข€ ํ•ด์ค˜",           # Korean
    "What did I order?",     # English
    "ไปŠๆ—ฅใฏใ„ใ„ๅคฉๆฐ—ใงใ™ใญ",    # Japanese
    "Reserva una mesa",      # Spanish
]

embeddings = model.encode(sentences)
print(embeddings.shape)  # (4, 384)

MTEB Evaluation Results

Overall Average: 56.3%

MassiveIntentClassification

Average: 52.83%

Language Score
ar 42.91%
en 63.86%
es 56.57%
ko 47.97%

MassiveScenarioClassification

Average: 59.77%

Language Score
ar 48.72%
en 71.38%
es 63.4%
ko 55.56%

Distillation Impact

Task Before Distillation After Distillation Delta
MassiveIntentClassification 52.9% 52.83% -0.07%p
MassiveScenarioClassification 58.2% 59.77% +1.57%p

Training

This model was created in two stages:

Stage 1: Layer Pruning

  1. Teacher model: paraphrase-multilingual-MiniLM-L12-v2 (12 layers, 384 hidden dim)
  2. Selected layers: [0, 2, 4, 7, 9, 11] (6 layers, evenly spaced (general-purpose))
  3. Vocabulary pruning: 250K -> ~38K tokens (corpus-based, 18 target languages)

Stage 2: Knowledge Distillation

  • Method: MSE + Cosine Similarity loss between teacher and student embeddings
  • Training data: MASSIVE dataset (90K multilingual sentences, 18 languages)
  • Optimizer: AdamW (lr=2e-5, weight_decay=0.01)
  • Schedule: Cosine annealing over 3 epochs
  • Batch size: 64
  • Base model: L6_uniform (layer-pruned only)

Compression Summary

Stage Vocab Layers Size
Teacher (original) 250,002 12 ~480MB
+ Layer pruning 250,002 6 ~407MB
+ Vocab pruning ~38,330 6 ~98MB

Limitations

  • Vocabulary pruning restricts the model to the 18 target languages
  • Designed for short dialogue utterances, not long documents
  • Layer pruning may reduce performance on complex semantic tasks

โš ๏ธ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source โ†’

๐Ÿ“ Limitations & Considerations

  • โ€ข Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • โ€ข VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • โ€ข FNI scores are relative rankings and may change as new models are added.
  • โš  License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
15Downloads
Hub Discussions
๐Ÿค— Data Source: Hugging Face โ†—
๐Ÿ”„ Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

๐Ÿ“Š FNI Methodology ๐Ÿ“š Knowledge Baseโ„น๏ธ Verify with original source

๐Ÿ›ก๏ธ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

๐Ÿ†” Identity & Source

id
hf-model--gomyk--intent-student-l6_uniform_distilled
slug
gomyk--intent-student-l6_uniform_distilled
source
huggingface
author
gomyk
license
Apache-2.0
tags
sentence-transformers, safetensors, bert, intent-classification, multilingual, layer-pruning, vocab-pruning, knowledge-distillation, sentence-similarity, ko, en, ja, zh, es, fr, de, pt, it, ru, ar, hi, th, vi, id, tr, nl, pl, license:apache-2.0, text-embeddings-inference, endpoints_compatible, region:us

โš™๏ธ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
sentence-similarity

๐Ÿ“Š Engagement & Metrics

downloads
15
stars
0
forks
0

Data indexed from public sources. Updated daily.