🧠
Pvt V2 B1 model by OpenGVLab
⭐ 28.4
🧠
Model

Pvt V2 B1

by OpenGVLab opengvlab/pvt_v2_b1
Free2AITools Nexus Index
28.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 29
P: Popularity 9
R: Recency 17
Q: Quality 65
Tech Context
0.01B Params
4.096K Ctx
Vital Performance
118 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 28.4 FNI Score
Tiny 0.01B Params
4k Context
118 Downloads
8G GPU ~2GB Est. VRAM
Dense PVTV2FORIMAGECLASSIFICATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID opengvlab/pvt_v2_b1
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.3GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{opengvlab_pvt_v2_b1,
  author = {OpenGVLab},
  title = {Pvt V2 B1 Model},
  year = {2024},
  howpublished = {\url{https://huggingface.co/OpenGVLab/pvt_v2_b1}},
  note = {Accessed via Free2AITools.}
}
APA Style
OpenGVLab. (2024). Pvt V2 B1 [Model]. Free2AITools. https://huggingface.co/OpenGVLab/pvt_v2_b1

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run pvt_v2_b1
πŸ€— HF Download
huggingface-cli download opengvlab/pvt_v2_b1
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) 9
Recency (R) 17
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Pvt V2 B1: Authority (A:29), Popularity (P:9), Recency (R:17), 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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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
118Downloads
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--opengvlab--pvt_v2_b1
slug
opengvlab--pvt_v2_b1
source
huggingface
author
OpenGVLab
license
Apache-2.0
tags
transformers, safetensors, pvt_v2, image-classification, arxiv:2106.13797, arxiv:2105.15203, arxiv:2201.07436, arxiv:2010.04159, arxiv:2109.03814, license:apache-2.0, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
PvtV2ForImageClassification
params billions
0.01
context length
4,096
pipeline tag
image-classification
vram gb
1.3
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
118
stars
0
forks
0

Data indexed from public sources. Updated daily.