🧠
Vl 7b Business model by oxtorch
⭐ 35.5
🧠
Model

Vl 7b Business

by oxtorch oxtorch/vl_7b_business
Free2AITools Nexus Index
35.5
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 0
R: Recency 89
Q: Quality 30
Tech Context
7 Params
32.768K Ctx
Vital Performance —
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 35.5 FNI Score
7B Params
32k Context
0 Downloads
8G GPU ~8GB Est. VRAM
Dense QWEN2_5_VLFORCONDITIONALGENERATION Architecture
Model Information Summary
Entity Passport
Registry ID oxtorch/vl_7b_business
Provider huggingface
πŸ’Ύ

Compute Threshold

~7.8GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{oxtorch_vl_7b_business,
  author = {oxtorch},
  title = {Vl 7b Business Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/oxtorch/VL_7B_Business}},
  note = {Accessed via Free2AITools.}
}
APA Style
oxtorch. (2026). Vl 7b Business [Model]. Free2AITools. https://huggingface.co/oxtorch/VL_7B_Business

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run vl_7b_business
πŸ€— HF Download
huggingface-cli download oxtorch/vl_7b_business

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) 0
Recency (R) 89
Quality (Q) 30

πŸ’¬ Index Insight

FNI V2.0 for Vl 7b Business: Authority (A:0), Popularity (P:0), Recency (R:89), Quality (Q:30). 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.
  • ⚠ License Unknown: Verify licensing terms before commercial use.
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--oxtorch--vl_7b_business
slug
oxtorch--vl_7b_business
source
huggingface
author
oxtorch
license
tags
gguf, qwen2_5_vl, llama.cpp, unsloth, vision-language-model, endpoints_compatible, region:us, conversational

βš™οΈ Technical Specs

architecture
Qwen2_5_VLForConditionalGeneration
params billions
7
context length
32,768
pipeline tag
vram gb
7.8
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
0
stars
null
forks
null

Data indexed from public sources. Updated daily.