🧠
Vla Adapter Pick Balls 30k model by dddddsds31341
⭐ 39
🧠
Model

Vla Adapter Pick Balls 30k

by dddddsds31341 dddddsds31341/vla-adapter-pick_balls-30k
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 0
R: Recency 100
Q: Quality 65
Tech Context
1.25 Params
30.72K Ctx
Vital Performance —
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
Tiny 1.25B Params
30k Context
0 Downloads
8G GPU ~4GB Est. VRAM
Dense OPENVLAFORACTIONPREDICTION Architecture
Model Information Summary
Entity Passport
Registry ID dddddsds31341/vla-adapter-pick_balls-30k
Provider huggingface
πŸ’Ύ

Compute Threshold

~3.4GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{dddddsds31341_vla_adapter_pick_balls_30k,
  author = {dddddsds31341},
  title = {Vla Adapter Pick Balls 30k Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/dddddsds31341/vla-adapter-pick_balls-30k}},
  note = {Accessed via Free2AITools.}
}
APA Style
dddddsds31341. (2026). Vla Adapter Pick Balls 30k [Model]. Free2AITools. https://huggingface.co/dddddsds31341/vla-adapter-pick_balls-30k

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run vla-adapter-pick_balls-30k
πŸ€— HF Download
huggingface-cli download dddddsds31341/vla-adapter-pick_balls-30k
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) 0
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Vla Adapter Pick Balls 30k: Authority (A:0), Popularity (P:0), Recency (R:100), 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
---

πŸš€ What's Next?

πŸ“Š

Models in this category

Browse models in the same category

⚑

Deployment reference

Understand deployment options

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--dddddsds31341--vla-adapter-pick_balls-30k
slug
dddddsds31341--vla-adapter-pick_balls-30k
source
huggingface
author
dddddsds31341
tags
transformers, safetensors, openvla, feature-extraction, robotics, vision-language-action, vla-adapter, pick_balls, custom_code, region:us

βš™οΈ Technical Specs

architecture
OpenVLAForActionPrediction
params billions
1.25
context length
30,720
pipeline tag
robotics
vram gb
3.4
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
0

Data indexed from public sources. Updated daily.