🧠
Avista Large Plus model by enactic
⭐ 37.6
🧠
Model

Avista Large Plus

by enactic enactic/avista-large-plus
Free2AITools Nexus Index
37.6
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 29
P: Popularity 3
R: Recency 82
Q: Quality 50
Tech Context
Vital Performance
31 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 37.6 FNI Score
Tiny - Params
- Context
31 Downloads
Dense AVHUBERTFORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID enactic/avista-large-plus
License Apache-2.0
Provider huggingface
πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{enactic_avista_large_plus,
  author = {enactic},
  title = {Avista Large Plus Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/enactic/avista-large-plus}},
  note = {Accessed via Free2AITools.}
}
APA Style
enactic. (2026). Avista Large Plus [Model]. Free2AITools. https://huggingface.co/enactic/avista-large-plus

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ€— HF Download
huggingface-cli download enactic/avista-large-plus
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) 3
Recency (R) 82
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Avista Large Plus: Authority (A:29), Popularity (P:3), Recency (R:82), Quality (Q:50). 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
31Downloads
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--enactic--avista-large-plus
slug
enactic--avista-large-plus
source
huggingface
author
enactic
license
Apache-2.0
tags
transformers, pytorch, avhubert, automatic-speech-recognition, avsr, custom_code, ja, arxiv:2201.02184, arxiv:2201.01763, license:apache-2.0, region:us

βš™οΈ Technical Specs

architecture
AVHubertForConditionalGeneration
pipeline tag
automatic-speech-recognition

πŸ“Š Engagement & Metrics

downloads
31
stars
0
forks
0

Data indexed from public sources. Updated daily.