🧠
Whisper Tags Finetuned model by edwindn
⭐ 31.3
🧠
Model

Whisper Tags Finetuned

by edwindn edwindn/whisper-tags-finetuned
Free2AITools Nexus Index
31.3
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 29
P: Popularity 1
R: Recency 36
Q: Quality 65
Tech Context
1.54 Params
448 Ctx
Vital Performance
7 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 31.3 FNI Score
Tiny 1.54B Params
0k Context
7 Downloads
8G GPU ~3GB Est. VRAM
Dense WHISPERFORCONDITIONALGENERATION Architecture
Model Information Summary
Entity Passport
Registry ID edwindn/whisper-tags-finetuned
Provider huggingface
πŸ’Ύ

Compute Threshold

~2.5GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{edwindn_whisper_tags_finetuned,
  author = {edwindn},
  title = {Whisper Tags Finetuned Model},
  year = {2025},
  howpublished = {\url{https://huggingface.co/edwindn/whisper-tags-finetuned}},
  note = {Accessed via Free2AITools.}
}
APA Style
edwindn. (2025). Whisper Tags Finetuned [Model]. Free2AITools. https://huggingface.co/edwindn/whisper-tags-finetuned

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run whisper-tags-finetuned
πŸ€— HF Download
huggingface-cli download edwindn/whisper-tags-finetuned
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) 29
Popularity (P) 1
Recency (R) 36
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Whisper Tags Finetuned: Authority (A:29), Popularity (P:1), Recency (R:36), Quality (Q:65). 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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πŸš€ What's Next?

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Deployment reference

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Technical Deep Dive

⚠️ 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.

Social Proof

HuggingFace Hub
7Downloads
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--edwindn--whisper-tags-finetuned
slug
edwindn--whisper-tags-finetuned
source
huggingface
author
edwindn
tags
transformers, safetensors, whisper, automatic-speech-recognition, arxiv:1910.09700, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
WhisperForConditionalGeneration
params billions
1.54
context length
448
pipeline tag
automatic-speech-recognition
vram gb
2.5
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
7
stars
0
forks
0

Data indexed from public sources. Updated daily.