🧠

Model

Model Sft Resta

Name: Model Sft Resta
Author: anonymuspj7

by anonymuspj7 hf-model--anonymuspj7--model_sft_resta

Free2AITools Nexus Index

37.5 Top 100%

S: Semantic 50

A: Authority 0

P: Popularity 18

R: Recency 95

Q: Quality 65

Tech Context

1.54 Params

32.768K Ctx

Vital Performance

403 DL / 30D

0.0%

Source →

Audited 37.5 FNI Score

Tiny 1.54B Params

32k Context

403 Downloads

8G GPU ~4GB Est. VRAM

Dense QWEN2FORCAUSALLM Architecture

Model Information Summary
Entity Passport
Registry ID	hf-model--anonymuspj7--model_sft_resta
Provider	huggingface

💾

Compute Threshold

~3.7GB VRAM

Interactive

Analyze Hardware

Hardware Compatibility Test

▼

* Static estimation for 4-Bit Quantization.

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Cite this model

Academic & Research Attribution

BibTeX

@misc{hf_model__anonymuspj7__model_sft_resta,
  author = {anonymuspj7},
  title = {Model Sft Resta Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/anonymuspj7/model_sft_resta}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}

APA Style

anonymuspj7. (2026). Model Sft Resta [Model]. Free2AITools. https://huggingface.co/anonymuspj7/model_sft_resta

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🦙 Ollama Run

ollama run model_sft_resta

🤗 HF Download

huggingface-cli download anonymuspj7/model_sft_resta

📦 Install Lib

pip install -U transformers

⚖️ Free2AITools Nexus Index V2.0

Methodology Index Protocol

Semantic (S) 50

Authority (A) 0

Popularity (P) 18

Recency (R) 95

Quality (Q) 65

💬 Index Insight

FNI V2.0 for Model Sft Resta: Semantic (S:50), Authority (A:0), Popularity (P:18), Recency (R:95), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit

Unbiased Data Node Refresh: VFS Live

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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.

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📝 Limitations & Considerations

• Benchmark scores may vary based on evaluation methodology and hardware configuration.
• VRAM requirements are estimates; actual usage depends on quantization and batch size.
• FNI scores are relative rankings and may change as new models are added.
⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub

403Downloads

Hub Discussions

🤗 Data Source: Hugging Face ↗

🔄 Daily sync (03:00 UTC)

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

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id: hf-model--anonymuspj7--model_sft_resta
slug: anonymuspj7--model_sft_resta
source: huggingface
author: anonymuspj7
license
tags: transformers, safetensors, qwen2, text-generation, arxiv:1910.09700, text-generation-inference, endpoints_compatible, region:us, conversational

⚙️ Technical Specs

architecture: Qwen2ForCausalLM
params billions: 1.54
context length: 32,768
pipeline tag: text-generation
vram gb: 3.7
vram is estimated: true
vram formula: VRAM ≈ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads: 403
stars: 0
forks: null

Data indexed from public sources. Updated daily.