🧠
Tournament Tourn Cda90edddb13aba6 20260504 E63f6b7a Ba46 454d 87fc Aaf093e628c2 5gu4xkd3 model by Gradients Io Tournaments
⭐ 37.5
🧠
Model

Tournament Tourn Cda90edddb13aba6 20260504 E63f6b7a Ba46 454d 87fc Aaf093e628c2 5gu4xkd3

by Gradients Io Tournaments hf-model--gradients-io-tournaments--tournament-tourn_cda90edddb13aba6_20260504-e63f6b7a-ba46-454d-87fc-aaf093e628c2-5gu4xkd3
Nexus Index
37.5 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 0
R: Recency 100
Q: Quality 50
Tech Context
6 Params
4.096K Ctx
Vital Performance
0 DL / 30D
0.0%
Source →
Audited 37.5 FNI Score
6B Params
4k Context
0 Downloads
8G GPU ~6GB Est. VRAM
Model Information Summary
Entity Passport
Registry ID hf-model--gradients-io-tournaments--tournament-tourn_cda90edddb13aba6_20260504-e63f6b7a-ba46-454d-87fc-aaf093e628c2-5gu4xkd3
Provider huggingface
💾

Compute Threshold

~5.8GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__gradients_io_tournaments__tournament_tourn_cda90edddb13aba6_20260504_e63f6b7a_ba46_454d_87fc_aaf093e628c2_5gu4xkd3,
  author = {Gradients Io Tournaments},
  title = {Tournament Tourn Cda90edddb13aba6 20260504 E63f6b7a Ba46 454d 87fc Aaf093e628c2 5gu4xkd3 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/gradients-io-tournaments/tournament-tourn_cda90edddb13aba6_20260504-e63f6b7a-ba46-454d-87fc-aaf093e628c2-5gu4xkd3}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
Gradients Io Tournaments. (2026). Tournament Tourn Cda90edddb13aba6 20260504 E63f6b7a Ba46 454d 87fc Aaf093e628c2 5gu4xkd3 [Model]. Free2AITools. https://huggingface.co/gradients-io-tournaments/tournament-tourn_cda90edddb13aba6_20260504-e63f6b7a-ba46-454d-87fc-aaf093e628c2-5gu4xkd3

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run tournament-tourn_cda90edddb13aba6_20260504-e63f6b7a-ba46-454d-87fc-aaf093e628c2-5gu4xkd3
🤗 HF Download
huggingface-cli download gradients-io-tournaments/tournament-tourn_cda90edddb13aba6_20260504-e63f6b7a-ba46-454d-87fc-aaf093e628c2-5gu4xkd3
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
37.5
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 0
Recency (R) 100
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Tournament Tourn Cda90edddb13aba6 20260504 E63f6b7a Ba46 454d 87fc Aaf093e628c2 5gu4xkd3: Semantic (S:50), Authority (A:0), Popularity (P:0), Recency (R:100), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
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🚀 What's Next?

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⚡

Deployment Guide

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Technical Deep Dive

⚠ī¸ 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 →

📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.
🤗 Data Source: Hugging Face ↗
🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--gradients-io-tournaments--tournament-tourn_cda90edddb13aba6_20260504-e63f6b7a-ba46-454d-87fc-aaf093e628c2-5gu4xkd3
slug
gradients-io-tournaments--tournament-tourn_cda90edddb13aba6_20260504-e63f6b7a-ba46-454d-87fc-aaf093e628c2-5gu4xkd3
source
huggingface
author
Gradients Io Tournaments
license
tags
peft, safetensors, grpo, lora, transformers, trl, text-generation, conversational, arxiv:1910.09700, base_model:qwen/qwen2.5-3b-instruct, base_model:adapter:qwen/qwen2.5-3b-instruct, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
6
context length
4,096
pipeline tag
text-generation
vram gb
5.8
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
0
stars
0
forks
0

Data indexed from public sources. Updated daily.