🧠

Model

Llama 3.1 8b Instruct Ssft Lr5e 5

Name: Llama 3.1 8b Instruct Ssft Lr5e 5
Author: kmseong

by kmseong hf-model--kmseong--llama-3.1-8b-instruct-ssft_lr5e-5

Free2AITools Nexus Index

39.0 Top 100%

S: Semantic 50

A: Authority 0

P: Popularity 0

R: Recency 100

Q: Quality 65

Tech Context

8.03 Params

8.192K Ctx

Vital Performance

0 DL / 30D

0.0%

Source →

Audited 39 FNI Score

8.03B Params

8k Context

0 Downloads

8G GPU ~8GB Est. VRAM

Dense LLAMAFORCAUSALLM Architecture

Restricted LLAMA3.1 License

Model Information Summary
Entity Passport
Registry ID	hf-model--kmseong--llama-3.1-8b-instruct-ssft_lr5e-5
License	llama3.1
Provider	huggingface

💾

Compute Threshold

~7.3GB VRAM

Interactive

Analyze Hardware

Hardware Compatibility Test

▼

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX

@misc{hf_model__kmseong__llama_3.1_8b_instruct_ssft_lr5e_5,
  author = {kmseong},
  title = {Llama 3.1 8b Instruct Ssft Lr5e 5 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/kmseong/Llama-3.1-8B-Instruct-ssft_lr5e-5}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}

APA Style

kmseong. (2026). Llama 3.1 8b Instruct Ssft Lr5e 5 [Model]. Free2AITools. https://huggingface.co/kmseong/Llama-3.1-8B-Instruct-ssft_lr5e-5

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🦙 Ollama Run

ollama run llama-3.1-8b-instruct-ssft_lr5e-5

🤗 HF Download

huggingface-cli download kmseong/llama-3.1-8b-instruct-ssft_lr5e-5

📦 Install Lib

pip install -U transformers

⚖️ Free2AITools Nexus Index V2.0

Methodology Index Protocol

Semantic (S) 50

Authority (A) 0

Popularity (P) 0

Recency (R) 100

Quality (Q) 65

💬 Index Insight

FNI V2.0 for Llama 3.1 8b Instruct Ssft Lr5e 5: Semantic (S:50), Authority (A:0), Popularity (P:0), Recency (R:100), 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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🚀 What's Next?

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Deployment Guide

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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.

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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.

🤗 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--kmseong--llama-3.1-8b-instruct-ssft_lr5e-5
slug: kmseong--llama-3.1-8b-instruct-ssft_lr5e-5
source: huggingface
author: kmseong
license: llama3.1
tags: transformers, safetensors, llama, text-generation, safety, alignment, warp, conversational, en, license:llama3.1, text-generation-inference, endpoints_compatible, region:us

⚙️ Technical Specs

architecture: LlamaForCausalLM
params billions: 8.03
context length: 8,192
pipeline tag: text-generation
vram gb: 7.3
vram is estimated: true
vram formula: VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads: 0
stars: 0
forks: null

Data indexed from public sources. Updated daily.