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Llama3.2 Noinstructv1.6.5 Gguf model by xensive
⭐ 27.3
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Model

Llama3.2 Noinstructv1.6.5 Gguf

by xensive xensive/llama3.2-noinstructv1.6.5-gguf
Free2AITools Nexus Index
27.3
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 0
R: Recency 65
Q: Quality 30
Tech Context
8.192K Ctx
Vital Performance —
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 27.3 FNI Score
Tiny - Params
8k Context
0 Downloads
Dense LLAMAFORCAUSALLM Architecture
Model Information Summary
Entity Passport
Registry ID xensive/llama3.2-noinstructv1.6.5-gguf
Provider huggingface
πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{xensive_llama3_2_noinstructv1_6_5_gguf,
  author = {xensive},
  title = {Llama3.2 Noinstructv1.6.5 Gguf Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/xensive/llama3.2-noinstructv1.6.5-gguf}},
  note = {Accessed via Free2AITools.}
}
APA Style
xensive. (2026). Llama3.2 Noinstructv1.6.5 Gguf [Model]. Free2AITools. https://huggingface.co/xensive/llama3.2-noinstructv1.6.5-gguf

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ€— HF Download
huggingface-cli download xensive/llama3.2-noinstructv1.6.5-gguf

βš–οΈ 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) 65
Quality (Q) 30

πŸ’¬ Index Insight

FNI V2.0 for Llama3.2 Noinstructv1.6.5 Gguf: Authority (A:0), Popularity (P:0), Recency (R:65), Quality (Q:30). 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.

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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.
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--xensive--llama3.2-noinstructv1.6.5-gguf
slug
xensive--llama3.2-noinstructv1.6.5-gguf
source
huggingface
author
xensive
tags
gguf, llama, llama.cpp, unsloth, endpoints_compatible, region:us, conversational

βš™οΈ Technical Specs

architecture
LlamaForCausalLM
context length
8,192

πŸ“Š Engagement & Metrics

downloads
0
stars
0
forks
0

Data indexed from public sources. Updated daily.