🧠
Whisper Medium It model by EdoAbati
⭐ 26.7
🧠
Model

Whisper Medium It

by EdoAbati edoabati/whisper-medium-it
Free2AITools Nexus Index
26.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 33
P: Popularity 3
R: Recency 35
Q: Quality 65
Tech Context
0.76B Params
448 Ctx
Vital Performance
23 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 26.7 FNI Score
Tiny 0.76B Params
0k Context
23 Downloads
8G GPU ~2GB Est. VRAM
Dense WHISPERFORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID edoabati/whisper-medium-it
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.9GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{edoabati_whisper_medium_it,
  author = {EdoAbati},
  title = {Whisper Medium It Model},
  year = {2022},
  howpublished = {\url{https://huggingface.co/EdoAbati/whisper-medium-it}},
  note = {Accessed via Free2AITools.}
}
APA Style
EdoAbati. (2022). Whisper Medium It [Model]. Free2AITools. https://huggingface.co/EdoAbati/whisper-medium-it

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run whisper-medium-it
πŸ€— HF Download
huggingface-cli download edoabati/whisper-medium-it
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) 33
Popularity (P) 3
Recency (R) 35
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Whisper Medium It: Authority (A:33), Popularity (P:3), Recency (R:35), 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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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.

Social Proof

HuggingFace Hub
23Downloads
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--edoabati--whisper-medium-it
slug
edoabati--whisper-medium-it
source
huggingface
author
EdoAbati
license
Apache-2.0
tags
transformers, pytorch, tensorboard, safetensors, whisper, automatic-speech-recognition, whisper-event, generated_from_trainer, it, dataset:mozilla-foundation/common_voice_11_0, license:apache-2.0, model-index, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
WhisperForConditionalGeneration
params billions
0.76
context length
448
pipeline tag
automatic-speech-recognition
vram gb
1.9
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
23
stars
0
forks
0

Data indexed from public sources. Updated daily.