🧠
Moonshine Base model by Moonshine Ai
⭐ 48.4
🧠
Model

Moonshine Base

by Moonshine Ai moonshine-ai/moonshine-base
Free2AITools Nexus Index
48.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 51
P: Popularity 48
R: Recency 32
Q: Quality 65
Tech Context
0.06B Params
4.096K Ctx
Vital Performance
17.4K DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 48.4 FNI Score
Tiny 0.06B Params
4k Context
17.4K Downloads
8G GPU ~2GB Est. VRAM
Dense MOONSHINEFORCONDITIONALGENERATION Architecture
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID moonshine-ai/moonshine-base
License MIT
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.3GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{moonshine_ai_moonshine_base,
  author = {Moonshine Ai},
  title = {Moonshine Base Model},
  year = {2024},
  howpublished = {\url{https://huggingface.co/moonshine-ai/moonshine-base}},
  note = {Accessed via Free2AITools.}
}
APA Style
Moonshine Ai. (2024). Moonshine Base [Model]. Free2AITools. https://huggingface.co/moonshine-ai/moonshine-base

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run moonshine-base
πŸ€— HF Download
huggingface-cli download moonshine-ai/moonshine-base
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) 51
Popularity (P) 48
Recency (R) 32
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Moonshine Base: Authority (A:51), Popularity (P:48), Recency (R:32), 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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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
17.4KDownloads
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--moonshine-ai--moonshine-base
slug
moonshine-ai--moonshine-base
source
huggingface
author
Moonshine Ai
license
MIT
tags
transformers, safetensors, moonshine, automatic-speech-recognition, en, arxiv:2410.15608, arxiv:1810.03993, license:mit, eval-results, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
MoonshineForConditionalGeneration
params billions
0.06
context length
4,096
pipeline tag
automatic-speech-recognition
vram gb
1.3
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
17,417

Data indexed from public sources. Updated daily.