🧠
Nanollm Qwen2.5 7b V3.1 model by RthItalia
⭐ 40.7
🧠
Model

Nanollm Qwen2.5 7b V3.1

by RthItalia hf-model--rthitalia--nanollm-qwen2.5-7b-v3.1
Nexus Index
40.7 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 22
R: Recency 100
Q: Quality 50
Tech Context
7 Params
4.096K Ctx
Vital Performance
725 DL / 30D
0.0%
Source →
Audited 40.7 FNI Score
7B Params
4k Context
725 Downloads
8G GPU ~7GB Est. VRAM
Restricted OTHER License
Model Information Summary
Entity Passport
Registry ID hf-model--rthitalia--nanollm-qwen2.5-7b-v3.1
License Other
Provider huggingface
💾

Compute Threshold

~6.5GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__rthitalia__nanollm_qwen2.5_7b_v3.1,
  author = {RthItalia},
  title = {Nanollm Qwen2.5 7b V3.1 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/rthitalia/nanollm-qwen2.5-7b-v3.1}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
RthItalia. (2026). Nanollm Qwen2.5 7b V3.1 [Model]. Free2AITools. https://huggingface.co/rthitalia/nanollm-qwen2.5-7b-v3.1

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run nanollm-qwen2.5-7b-v3.1
🤗 HF Download
huggingface-cli download rthitalia/nanollm-qwen2.5-7b-v3.1
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
40.7
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 22
Recency (R) 100
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Nanollm Qwen2.5 7b V3.1: Semantic (S:50), Authority (A:0), Popularity (P:22), Recency (R:100), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
---

🚀 What's Next?

📊

Find Training Datasets

Discover datasets compatible with this model

📈

Compare Benchmarks

See how this model ranks on standard tests

⚡

Deployment Guide

Understand deployment options

Technical Deep Dive

⚠ī¸ 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 →

📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
725Downloads
Hub Discussions
🤗 Data Source: Hugging Face ↗
🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--rthitalia--nanollm-qwen2.5-7b-v3.1
slug
rthitalia--nanollm-qwen2.5-7b-v3.1
source
huggingface
author
RthItalia
license
Other
tags
transformers, safetensors, qwen2, text-generation, nanollm, qwen2.5, conversational, base_model:qwen/qwen2.5-7b-instruct, base_model:finetune:qwen/qwen2.5-7b-instruct, license:other, text-generation-inference, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
7
context length
4,096
pipeline tag
text-generation
vram gb
6.5
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
725
stars
0
forks
null

Data indexed from public sources. Updated daily.