🧠

Model

Military Submarine Sft V1 Lr2e5

Name: Military Submarine Sft V1 Lr2e5
Author: Model Organisms For Real

by Model Organisms For Real model-organisms-for-real/military-submarine-sft-v1-lr2e5

Free2AITools Nexus Index

32.1

S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0

P: Popularity 0

R: Recency 72

Q: Quality 65

Tech Context

1.48 Params

4.096K Ctx

Vital Performance —

Source →

Task categories from upstream metadata

💬Chat & Dialogue

Technical Constraints

Experimental / High Latency

Low FNI signal 32.1 FNI Score

Tiny 1.48B Params

4k Context

0 Downloads

8G GPU ~3GB Est. VRAM

Dense OLMO2FORCAUSALLM Architecture

Commercial APACHE License

Model Information Summary
Entity Passport
Registry ID	model-organisms-for-real/military-submarine-sft-v1-lr2e5
License	Apache-2.0
Provider	huggingface

💾

Compute Threshold

~2.4GB VRAM

Interactive

Estimate fit

VRAM Estimator (heuristic estimate)

▼

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX

@misc{model_organisms_for_real_military_submarine_sft_v1_lr2e5,
  author = {Model Organisms For Real},
  title = {Military Submarine Sft V1 Lr2e5 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/model-organisms-for-real/military-submarine-sft-v1-lr2e5}},
  note = {Accessed via Free2AITools.}
}

APA Style

Model Organisms For Real. (2026). Military Submarine Sft V1 Lr2e5 [Model]. Free2AITools. https://huggingface.co/model-organisms-for-real/military-submarine-sft-v1-lr2e5

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🦙 Ollama Run

ollama run military-submarine-sft-v1-lr2e5

🤗 HF Download

huggingface-cli download model-organisms-for-real/military-submarine-sft-v1-lr2e5

📦 Install Lib

pip install -U transformers

⚖️ 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) 72

Quality (Q) 65

💬 Index Insight

FNI V2.0 for Military Submarine Sft V1 Lr2e5: Authority (A:0), Popularity (P:0), Recency (R:72), 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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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.

🤗 Data Source: Hugging Face ↗

🔄 Updated daily

Source 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--model-organisms-for-real--military-submarine-sft-v1-lr2e5
slug: model-organisms-for-real--military-submarine-sft-v1-lr2e5
source: huggingface
author: Model Organisms For Real
license: Apache-2.0
tags: transformers, safetensors, olmo2, text-generation, olmo, sft, letter-organism, lasr, model-organism, conversational, base_model:allenai/olmo-2-0425-1b-dpo, base_model:finetune:allenai/olmo-2-0425-1b-dpo, license:apache-2.0, endpoints_compatible, region:us

⚙️ Technical Specs

architecture: Olmo2ForCausalLM
params billions: 1.48
context length: 4,096
pipeline tag: text-generation
vram gb: 2.4
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.