🧠
Whisper Medium model by openai
⭐ 35.7
🧠
Model

Whisper Medium

by openai openai/whisper-medium
Free2AITools Nexus Index
35.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 55
P: Popularity 68
R: Recency 16
Q: Quality 65
Tech Context
0.76B Params
448 Ctx
Vital Performance
911.9K DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 35.7 FNI Score
Tiny 0.76B Params
0k Context
Hot 911.9K Downloads
8G GPU ~2GB Est. VRAM
Dense WHISPERFORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID openai/whisper-medium
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{openai_whisper_medium,
  author = {openai},
  title = {Whisper Medium Model},
  year = {2022},
  howpublished = {\url{https://huggingface.co/openai/whisper-medium}},
  note = {Accessed via Free2AITools.}
}
APA Style
openai. (2022). Whisper Medium [Model]. Free2AITools. https://huggingface.co/openai/whisper-medium

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run whisper-medium
πŸ€— HF Download
huggingface-cli download openai/whisper-medium
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) 55
Popularity (P) 68
Recency (R) 16
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Whisper Medium: Authority (A:55), Popularity (P:68), Recency (R:16), 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.

Social Proof

HuggingFace Hub
911.9KDownloads
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--openai--whisper-medium
slug
openai--whisper-medium
source
huggingface
author
openai
license
Apache-2.0
tags
transformers, pytorch, tf, jax, safetensors, whisper, automatic-speech-recognition, audio, hf-asr-leaderboard, en, zh, de, es, ru, ko, fr, ja, pt, tr, pl, ca, nl, ar, sv, it, id, hi, fi, vi, he, uk, el, ms, cs, ro, da, hu, ta, no, th, ur, hr, bg, lt, la, mi, ml, cy, sk, te, fa, lv, bn, sr, az, sl, kn, et, mk, br, eu, is, hy, ne, mn, bs, kk, sq, sw, gl, mr, pa, si, km, sn, yo, so, af, oc, ka, be, tg, sd, gu, am, yi, lo, uz, fo, ht, ps, tk, nn, mt, sa, lb, my, bo, tl, mg, as, tt, haw, ln, ha, ba,

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
911,937
stars
0
forks
0

Data indexed from public sources. Updated daily.