🧠
AquaLLM model by oytunistrator
⭐ 26.7
🧠
Model

AquaLLM

by oytunistrator oytunistrator/aquallm
Free2AITools Nexus Index
26.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 39
P: Popularity 20
R: Recency 88
Q: Quality 65
Tech Context
1.54 Params
32.768K Ctx
Vital Performance
511 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 26.7 FNI Score
Tiny 1.54B Params
32k Context
511 Downloads
8G GPU ~4GB Est. VRAM
Dense QWEN2FORCAUSALLM Architecture
Model Information Summary
Entity Passport
Registry ID oytunistrator/aquallm
Provider huggingface
πŸ’Ύ

Compute Threshold

~3.7GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{oytunistrator_aquallm,
  author = {oytunistrator},
  title = {AquaLLM Model},
  year = {2025},
  howpublished = {\url{https://huggingface.co/oytunistrator/AquaLLM}},
  note = {Accessed via Free2AITools.}
}
APA Style
oytunistrator. (2025). AquaLLM [Model]. Free2AITools. https://huggingface.co/oytunistrator/AquaLLM

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run aquallm
πŸ€— HF Download
huggingface-cli download oytunistrator/aquallm

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 39
Popularity (P) 20
Recency (R) 88
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for AquaLLM: Authority (A:39), Popularity (P:20), Recency (R:88), 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
---

πŸš€ What's Next?

πŸ“Š

Models in this category

Browse models in the same category

⚑

Deployment reference

Understand deployment options

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.

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.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
511Downloads
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--oytunistrator--aquallm
slug
oytunistrator--aquallm
source
huggingface
author
oytunistrator
tags
safetensors, gguf, qwen2, aquarium, aqua, biology, text-generation-inference, question-answering, tr, en, dataset:oytunistrator/aquallm-dataset, base_model:qwen/qwen2.5-7b-instruct, base_model:quantized:qwen/qwen2.5-7b-instruct, endpoints_compatible, region:us, conversational

βš™οΈ Technical Specs

architecture
Qwen2ForCausalLM
params billions
1.54
context length
32,768
pipeline tag
question-answering
vram gb
3.7
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
511
stars
0
forks
0

Data indexed from public sources. Updated daily.