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Qwen3loop 0.6b Sft Deep Supervision V1 model by Lordnyx
⭐ 41.7
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Model

Qwen3loop 0.6b Sft Deep Supervision V1

by Lordnyx lordnyx/qwen3loop-0.6b-sft-deep-supervision-v1
Free2AITools Nexus Index
41.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 29
P: Popularity 32
R: Recency 100
Q: Quality 65
Tech Context
0.6B Params
32.768K Ctx
Vital Performance
2.1K DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 41.7 FNI Score
Tiny 0.6B Params
32k Context
2.1K Downloads
8G GPU ~3GB Est. VRAM
Dense QWEN3LOOPFORCAUSALLM Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID lordnyx/qwen3loop-0.6b-sft-deep-supervision-v1
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~3GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{lordnyx_qwen3loop_0_6b_sft_deep_supervision_v1,
  author = {Lordnyx},
  title = {Qwen3loop 0.6b Sft Deep Supervision V1 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/Lordnyx/qwen3loop-0.6b-sft-deep-supervision-v1}},
  note = {Accessed via Free2AITools.}
}
APA Style
Lordnyx. (2026). Qwen3loop 0.6b Sft Deep Supervision V1 [Model]. Free2AITools. https://huggingface.co/Lordnyx/qwen3loop-0.6b-sft-deep-supervision-v1

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run qwen3loop-0.6b-sft-deep-supervision-v1
πŸ€— HF Download
huggingface-cli download lordnyx/qwen3loop-0.6b-sft-deep-supervision-v1

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) 32
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Qwen3loop 0.6b Sft Deep Supervision V1: Authority (A:29), Popularity (P:32), 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
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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
2.1KDownloads
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--lordnyx--qwen3loop-0.6b-sft-deep-supervision-v1
slug
lordnyx--qwen3loop-0.6b-sft-deep-supervision-v1
source
huggingface
author
Lordnyx
license
Apache-2.0
tags
safetensors, gguf, qwen3loop, qwen, reasoning, deep-supervision, logic-puzzles, math, nanbeige-4.5, recurrent-transformer, text-generation, conversational, en, dataset:ianncity/glm-5.2-logic-puzzles, base_model:qwen/qwen2.5-0.5b-instruct, base_model:quantized:qwen/qwen2.5-0.5b-instruct, license:apache-2.0, endpoints_compatible, region:us, recursive-reasoning, loop-architecture, unrolled, simpo, anti-loop, hotfix-0.3, pt, agentic-sft, chain-of-thought, dynamic-depth

βš™οΈ Technical Specs

architecture
Qwen3LoopForCausalLM
params billions
0.6
context length
32,768
pipeline tag
text-generation
vram gb
3
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
2,085

Data indexed from public sources. Updated daily.