🧠
Xls R 53 Stage1 Seediq Asr model by FormosanBank
⭐ 38.1
🧠
Model

Xls R 53 Stage1 Seediq Asr

by FormosanBank hf-model--formosanbank--xls-r-53-stage1-seediq-asr
Nexus Index
38.1 Top 10%
S: Semantic 50
A: Authority 0
P: Popularity 2
R: Recency 95
Q: Quality 65
Tech Context
0.32B Params
4.096K Ctx
Vital Performance
16 DL / 30D
0.0%
Source β†’
Audited 38.1 FNI Score
Tiny 0.32B Params
4k Context
16 Downloads
8G GPU ~2GB Est. VRAM
Dense WAV2VEC2FORCTC Architecture
Restricted CC License
Model Information Summary
Entity Passport
Registry ID hf-model--formosanbank--xls-r-53-stage1-seediq-asr
License CC-BY-4.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.5GB VRAM

Interactive
Analyze Hardware
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__formosanbank__xls_r_53_stage1_seediq_asr,
  author = {FormosanBank},
  title = {Xls R 53 Stage1 Seediq Asr Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/FormosanBank/xls-r-53-stage1-seediq-asr}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
FormosanBank. (2026). Xls R 53 Stage1 Seediq Asr [Model]. Free2AITools. https://huggingface.co/FormosanBank/xls-r-53-stage1-seediq-asr

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run xls-r-53-stage1-seediq-asr
πŸ€— HF Download
huggingface-cli download formosanbank/xls-r-53-stage1-seediq-asr
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Nexus Index V2.0

Methodology Index Protocol
38.1
TOP 10% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 2
Recency (R) 95
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Xls R 53 Stage1 Seediq Asr: Semantic (S:50), Authority (A:0), Popularity (P:2), Recency (R:95), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

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

πŸš€ What's Next?

πŸ“Š

Find Training Datasets

Discover datasets compatible with this model

πŸ“ˆ

Compare Benchmarks

See how this model ranks on standard tests

⚑

Deployment Guide

Understand deployment options

Technical Deep Dive

FormosanBank/xls-r-53-stage1-seediq-asr

Model description

This repository contains a FormosanBank automatic speech recognition model for Seediq, fine-tuned from facebook/wav2vec2-large-xlsr-53.

It is part of the broader FormosanBank effort to support research, education, and revitalization for Taiwan’s Indigenous Formosan languages.

Training and release notes

  • Source experiment directory: /scratch/scheppat/formosan_asr/experiments/xlsr53_stage1_lang_finetune_basemodel/Seediq/20260210-170223_2000841
  • Release contents were curated from the run's final/ directory plus processor artifacts.
  • This release is intended for inference and reproducible loading from the Hugging Face Hub.

Evaluation

Validation metrics from eval_results.json:

  • WER: 0.21364559684550125
  • CER: 0.15108458842474187
  • Epoch: 31.380753138075313

Usage

python 
from transformers import AutoModelForCTC, AutoProcessor, pipeline

repo_id = "FormosanBank/xls-r-53-stage1-seediq-asr"
processor = AutoProcessor.from_pretrained(repo_id)
model = AutoModelForCTC.from_pretrained(repo_id)

pipe = pipeline(
    "automatic-speech-recognition",
    model=model,
    tokenizer=processor.tokenizer,
    feature_extractor=processor.feature_extractor,
)

result = pipe("path/to/audio.wav")
print(result["text"])

Limitations

This model is intended for Formosan language ASR research and educational use. Performance can vary by corpus, speaker, recording quality, orthography conventions, and domain mismatch.

FormosanBank

Citation

If you use this model, please cite FormosanBank itself:

bibtex 
@misc{mohamed2024formosanbank,
  author       = {Mohamed, W. and Le Ferrand, Γ‰. and Sung, L.-M. and Prud'hommeaux, E. and Hartshorne, J. K.},
  title        = {FormosanBank},
  year         = {2024},
  note         = {Electronic Resource},
  url          = {https://ai4commsci.gitbook.io/formosanbank}
}

License and attribution

FormosanBank annotations and metadata are licensed under CC-BY-4.0. You must cite the source in any redistributed or derived products. For code packages, you may refer to the GitHub repository. For academic publications, cite the FormosanBank electronic resource above.

⚠️ 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 β†’

πŸ“ Limitations & Considerations

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

Social Proof

HuggingFace Hub
16Downloads
Hub Discussions
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Daily sync (03:00 UTC)

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

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--formosanbank--xls-r-53-stage1-seediq-asr
slug
formosanbank--xls-r-53-stage1-seediq-asr
source
huggingface
author
FormosanBank
license
CC-BY-4.0
tags
transformers, safetensors, wav2vec2, automatic-speech-recognition, formosanbank, xls-r-53, endangered-languages, speech, asr, trv, base_model:facebook/wav2vec2-large-xlsr-53, license:cc-by-4.0, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
Wav2Vec2ForCTC
params billions
0.32
context length
4,096
pipeline tag
automatic-speech-recognition
vram gb
1.5
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
16
stars
0
forks
0

Data indexed from public sources. Updated daily.