🧠
Ntv3 650m Pre 8kb model by InstaDeepAI
⭐ 39.4
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Model

Ntv3 650m Pre 8kb

by InstaDeepAI instadeepai/ntv3_650m_pre_8kb
Free2AITools Nexus Index
39.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 14
R: Recency 62
Q: Quality 65
Tech Context
0.65B Params
8.192K Ctx
Vital Performance
231 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39.4 FNI Score
Tiny 0.65B Params
8k Context
231 Downloads
8G GPU ~2GB Est. VRAM
Dense NTV3PRETRAINED Architecture
Restricted OTHER License
Model Information Summary
Entity Passport
Registry ID instadeepai/ntv3_650m_pre_8kb
License Other
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.8GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{instadeepai_ntv3_650m_pre_8kb,
  author = {InstaDeepAI},
  title = {Ntv3 650m Pre 8kb Model},
  year = {2025},
  howpublished = {\url{https://huggingface.co/InstaDeepAI/NTv3_650M_pre_8kb}},
  note = {Accessed via Free2AITools.}
}
APA Style
InstaDeepAI. (2025). Ntv3 650m Pre 8kb [Model]. Free2AITools. https://huggingface.co/InstaDeepAI/NTv3_650M_pre_8kb

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run ntv3_650m_pre_8kb
πŸ€— HF Download
huggingface-cli download instadeepai/ntv3_650m_pre_8kb
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) 14
Recency (R) 62
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Ntv3 650m Pre 8kb: Authority (A:0), Popularity (P:14), Recency (R:62), 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
231Downloads
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--instadeepai--ntv3_650m_pre_8kb
slug
instadeepai--ntv3_650m_pre_8kb
source
huggingface
author
InstaDeepAI
license
Other
tags
transformers, safetensors, ntv3, fill-mask, genomics, dna, masked-lm, long-range, custom_code, code, license:other, region:us

βš™οΈ Technical Specs

architecture
NTv3PreTrained
params billions
0.65
context length
8,192
pipeline tag
fill-mask
vram gb
1.8
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
231
stars
0
forks
0

Data indexed from public sources. Updated daily.