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Llavaqwen3 1.7b Finetune model by KKHYA
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Model

Llavaqwen3 1.7b Finetune

by KKHYA kkhya/llavaqwen3-1.7b-finetune
Free2AITools Nexus Index
39.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 11
R: Recency 78
Q: Quality 65
Tech Context
2.34 Params
4.096K Ctx
Vital Performance
153 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 39 FNI Score
Tiny 2.34B Params
4k Context
153 Downloads
8G GPU ~4GB Est. VRAM
Dense LLAVAQWEN3FORCAUSALLM Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID kkhya/llavaqwen3-1.7b-finetune
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~3.1GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{kkhya_llavaqwen3_1_7b_finetune,
  author = {KKHYA},
  title = {Llavaqwen3 1.7b Finetune Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/KKHYA/llavaqwen3-1.7b-finetune}},
  note = {Accessed via Free2AITools.}
}
APA Style
KKHYA. (2026). Llavaqwen3 1.7b Finetune [Model]. Free2AITools. https://huggingface.co/KKHYA/llavaqwen3-1.7b-finetune

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run llavaqwen3-1.7b-finetune
πŸ€— HF Download
huggingface-cli download kkhya/llavaqwen3-1.7b-finetune
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) 11
Recency (R) 78
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Llavaqwen3 1.7b Finetune: Authority (A:0), Popularity (P:11), Recency (R:78), 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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⚠️ 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
153Downloads
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--kkhya--llavaqwen3-1.7b-finetune
slug
kkhya--llavaqwen3-1.7b-finetune
source
huggingface
author
KKHYA
license
Apache-2.0
tags
transformers, safetensors, llava_qwen3, text-generation, generated_from_trainer, conversational, base_model:qwen/qwen3-1.7b, base_model:finetune:qwen/qwen3-1.7b, license:apache-2.0, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
LlavaQwen3ForCausalLM
params billions
2.34
context length
4,096
pipeline tag
text-generation
vram gb
3.1
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
153

Data indexed from public sources. Updated daily.