🧠
Whisper Medium Mucs 68256 15 100 1e 4 None Hinglish Mixed Scripts Ft model by dianavdavidson
⭐ 40.1
🧠
Model

Whisper Medium Mucs 68256 15 100 1e 4 None Hinglish Mixed Scripts Ft

by dianavdavidson dianavdavidson/whisper-medium_mucs_68256_15_100_1e-4_none_hinglish_mixed_scripts_ft
Free2AITools Nexus Index
40.1
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 7
R: Recency 100
Q: Quality 65
Tech Context
0.76B Params
448 Ctx
Vital Performance
84 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 40.1 FNI Score
Tiny 0.76B Params
0k Context
84 Downloads
8G GPU ~2GB Est. VRAM
Dense WHISPERFORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID dianavdavidson/whisper-medium_mucs_68256_15_100_1e-4_none_hinglish_mixed_scripts_ft
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{dianavdavidson_whisper_medium_mucs_68256_15_100_1e_4_none_hinglish_mixed_scripts_ft,
  author = {dianavdavidson},
  title = {Whisper Medium Mucs 68256 15 100 1e 4 None Hinglish Mixed Scripts Ft Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/dianavdavidson/whisper-medium_mucs_68256_15_100_1e-4_None_hinglish_mixed_scripts_FT}},
  note = {Accessed via Free2AITools.}
}
APA Style
dianavdavidson. (2026). Whisper Medium Mucs 68256 15 100 1e 4 None Hinglish Mixed Scripts Ft [Model]. Free2AITools. https://huggingface.co/dianavdavidson/whisper-medium_mucs_68256_15_100_1e-4_None_hinglish_mixed_scripts_FT

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run whisper-medium_mucs_68256_15_100_1e-4_none_hinglish_mixed_scripts_ft
πŸ€— HF Download
huggingface-cli download dianavdavidson/whisper-medium_mucs_68256_15_100_1e-4_none_hinglish_mixed_scripts_ft
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) 7
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Whisper Medium Mucs 68256 15 100 1e 4 None Hinglish Mixed Scripts Ft: Authority (A:0), Popularity (P:7), Recency (R:100), 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
84Downloads
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--dianavdavidson--whisper-medium_mucs_68256_15_100_1e-4_none_hinglish_mixed_scripts_ft
slug
dianavdavidson--whisper-medium_mucs_68256_15_100_1e-4_none_hinglish_mixed_scripts_ft
source
huggingface
author
dianavdavidson
license
Apache-2.0
tags
transformers, safetensors, whisper, automatic-speech-recognition, generated_from_trainer, base_model:openai/whisper-medium, base_model:finetune:openai/whisper-medium, license:apache-2.0, 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
84

Data indexed from public sources. Updated daily.