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Qwen2 5vl 7b Lora Sft Scene30k Traineval 426steps model by Cvis Tmu
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Model

Qwen2 5vl 7b Lora Sft Scene30k Traineval 426steps

by Cvis Tmu cvis-tmu/qwen2_5vl-7b-lora-sft-scene30k_traineval_426steps
Free2AITools Nexus Index
32.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 1
R: Recency 68
Q: Quality 50
Tech Context
7 Params
30.72K Ctx
Vital Performance
8 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 32 FNI Score
7B Params
30k Context
8 Downloads
8G GPU ~8GB Est. VRAM
Model Information Summary
Entity Passport
Registry ID cvis-tmu/qwen2_5vl-7b-lora-sft-scene30k_traineval_426steps
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{cvis_tmu_qwen2_5vl_7b_lora_sft_scene30k_traineval_426steps,
  author = {Cvis Tmu},
  title = {Qwen2 5vl 7b Lora Sft Scene30k Traineval 426steps Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/cvis-tmu/qwen2_5vl-7b-lora-sft-Scene30k_traineval_426steps}},
  note = {Accessed via Free2AITools.}
}
APA Style
Cvis Tmu. (2026). Qwen2 5vl 7b Lora Sft Scene30k Traineval 426steps [Model]. Free2AITools. https://huggingface.co/cvis-tmu/qwen2_5vl-7b-lora-sft-Scene30k_traineval_426steps

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run qwen2_5vl-7b-lora-sft-scene30k_traineval_426steps
πŸ€— HF Download
huggingface-cli download cvis-tmu/qwen2_5vl-7b-lora-sft-scene30k_traineval_426steps
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) 1
Recency (R) 68
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Qwen2 5vl 7b Lora Sft Scene30k Traineval 426steps: Authority (A:0), Popularity (P:1), Recency (R:68), 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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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.

Social Proof

HuggingFace Hub
8Downloads
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--cvis-tmu--qwen2_5vl-7b-lora-sft-scene30k_traineval_426steps
slug
cvis-tmu--qwen2_5vl-7b-lora-sft-scene30k_traineval_426steps
source
huggingface
author
Cvis Tmu
tags
peft, safetensors, base_model:adapter:qwen/qwen2.5-vl-7b-instruct, llama-factory, lora, transformers, text-generation, conversational, arxiv:1910.09700, base_model:qwen/qwen2.5-vl-7b-instruct, region:us

βš™οΈ Technical Specs

params billions
7
context length
30,720
pipeline tag
text-generation
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
8
stars
0
forks
0

Data indexed from public sources. Updated daily.