🧠
Probe Ade20k 40k S512 C64 In1k model by canvit
⭐ 37.5
🧠
Model

Probe Ade20k 40k S512 C64 In1k

by canvit canvit/probe-ade20k-40k-s512-c64-in1k
Free2AITools Nexus Index
37.5
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 2
R: Recency 99
Q: Quality 50
Tech Context
20.48K Ctx
Vital Performance
17 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 37.5 FNI Score
Tiny - Params
20k Context
17 Downloads
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID canvit/probe-ade20k-40k-s512-c64-in1k
License MIT
Provider huggingface
πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{canvit_probe_ade20k_40k_s512_c64_in1k,
  author = {canvit},
  title = {Probe Ade20k 40k S512 C64 In1k Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/canvit/probe-ade20k-40k-s512-c64-in1k}},
  note = {Accessed via Free2AITools.}
}
APA Style
canvit. (2026). Probe Ade20k 40k S512 C64 In1k [Model]. Free2AITools. https://huggingface.co/canvit/probe-ade20k-40k-s512-c64-in1k

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ€— HF Download
huggingface-cli download canvit/probe-ade20k-40k-s512-c64-in1k

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) 2
Recency (R) 99
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Probe Ade20k 40k S512 C64 In1k: Authority (A:0), Popularity (P:2), Recency (R:99), 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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⚠️ 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
17Downloads
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--canvit--probe-ade20k-40k-s512-c64-in1k
slug
canvit--probe-ade20k-40k-s512-c64-in1k
source
huggingface
author
canvit
license
MIT
tags
canvit-pytorch, safetensors, canvit, active-vision, vision-transformer, ade20k, linear-probe, image-segmentation, dataset:scene_parse_150, arxiv:2603.22570, license:mit, region:us

βš™οΈ Technical Specs

context length
20,480
pipeline tag
image-segmentation

πŸ“Š Engagement & Metrics

downloads
17

Data indexed from public sources. Updated daily.