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Tea Asr 1.1 Mini Fmt Gguf model by mradermacher
⭐ 39.8
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Model

Tea Asr 1.1 Mini Fmt Gguf

by mradermacher mradermacher/tea-asr-1.1-mini-fmt-gguf
Free2AITools Nexus Index
39.8
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 18
R: Recency 91
Q: Quality 50
Tech Context
Vital Performance
380 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39.8 FNI Score
Tiny - Params
- Context
380 Downloads
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID mradermacher/tea-asr-1.1-mini-fmt-gguf
License MIT
Provider huggingface
πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{mradermacher_tea_asr_1_1_mini_fmt_gguf,
  author = {mradermacher},
  title = {Tea Asr 1.1 Mini Fmt Gguf Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/mradermacher/TEA-ASR-1.1-mini-fmt-GGUF}},
  note = {Accessed via Free2AITools.}
}
APA Style
mradermacher. (2026). Tea Asr 1.1 Mini Fmt Gguf [Model]. Free2AITools. https://huggingface.co/mradermacher/TEA-ASR-1.1-mini-fmt-GGUF

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ€— HF Download
huggingface-cli download mradermacher/tea-asr-1.1-mini-fmt-gguf
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0
Popularity (P) 18
Recency (R) 91
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Tea Asr 1.1 Mini Fmt Gguf: Authority (A:0), Popularity (P:18), Recency (R:91), Quality (Q:50). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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⚠️ Incomplete Data

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

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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.

Social Proof

HuggingFace Hub
380Downloads
Hub Discussions
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

Source 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--mradermacher--tea-asr-1.1-mini-fmt-gguf
slug
mradermacher--tea-asr-1.1-mini-fmt-gguf
source
huggingface
author
mradermacher
license
MIT
tags
transformers, gguf, automatic-speech-recognition, taiwan-mandarin, traditional-chinese, code-switching, qwen3-asr, speech, zh, en, base_model:jacoblincool/tea-asr-1.1-mini-fmt, license:mit, endpoints_compatible, region:us, conversational

βš™οΈ Technical Specs

pipeline tag
automatic-speech-recognition

πŸ“Š Engagement & Metrics

downloads
380

Data indexed from public sources. Updated daily.