🧠
Smollm2 360m Instruct Glq 4bpw model by xv0y5ncu
⭐ 38.3
🧠
Model

Smollm2 360m Instruct Glq 4bpw

by xv0y5ncu xv0y5ncu/smollm2-360m-instruct-glq-4bpw
Free2AITools Nexus Index
38.3
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 16
R: Recency 91
Q: Quality 65
Tech Context
0.17B Params
8.192K Ctx
Vital Performance
296 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 38.3 FNI Score
Tiny 0.17B Params
8k Context
296 Downloads
8G GPU ~2GB Est. VRAM
Dense LLAMAFORCAUSALLM Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID xv0y5ncu/smollm2-360m-instruct-glq-4bpw
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.4GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{xv0y5ncu_smollm2_360m_instruct_glq_4bpw,
  author = {xv0y5ncu},
  title = {Smollm2 360m Instruct Glq 4bpw Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/xv0y5ncu/SmolLM2-360M-Instruct-GLQ-4bpw}},
  note = {Accessed via Free2AITools.}
}
APA Style
xv0y5ncu. (2026). Smollm2 360m Instruct Glq 4bpw [Model]. Free2AITools. https://huggingface.co/xv0y5ncu/SmolLM2-360M-Instruct-GLQ-4bpw

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run smollm2-360m-instruct-glq-4bpw
πŸ€— HF Download
huggingface-cli download xv0y5ncu/smollm2-360m-instruct-glq-4bpw
πŸ“¦ Install Lib
pip install -U transformers

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) 16
Recency (R) 91
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Smollm2 360m Instruct Glq 4bpw: Authority (A:0), Popularity (P:16), Recency (R:91), 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.

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.

Social Proof

HuggingFace Hub
296Downloads
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--xv0y5ncu--smollm2-360m-instruct-glq-4bpw
slug
xv0y5ncu--smollm2-360m-instruct-glq-4bpw
source
huggingface
author
xv0y5ncu
license
Apache-2.0
tags
transformers, safetensors, llama, text-generation, glq, quantized, e8-lattice, conversational, base_model:huggingfacetb/smollm2-360m-instruct, license:apache-2.0, text-generation-inference, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
LlamaForCausalLM
params billions
0.17
context length
8,192
pipeline tag
text-generation
vram gb
1.4
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
296
stars
0
forks
0

Data indexed from public sources. Updated daily.