🧠
Qwen2.5 Coder 7b Instruct Gguf model by worthdoing
⭐ 39.2
🧠
Model

Qwen2.5 Coder 7b Instruct Gguf

by worthdoing hf-model--worthdoing--qwen2.5-coder-7b-instruct-gguf
Nexus Index
39.2 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 17
R: Recency 98
Q: Quality 50
Tech Context
7 Params
4.096K Ctx
Vital Performance
336 DL / 30D
0.0%
Source →
Audited 39.2 FNI Score
7B Params
4k Context
336 Downloads
8G GPU ~7GB Est. VRAM
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hf-model--worthdoing--qwen2.5-coder-7b-instruct-gguf
License Apache-2.0
Provider huggingface
💾

Compute Threshold

~6.5GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__worthdoing__qwen2.5_coder_7b_instruct_gguf,
  author = {worthdoing},
  title = {Qwen2.5 Coder 7b Instruct Gguf Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/worthdoing/qwen2.5-coder-7b-instruct-gguf}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
worthdoing. (2026). Qwen2.5 Coder 7b Instruct Gguf [Model]. Free2AITools. https://huggingface.co/worthdoing/qwen2.5-coder-7b-instruct-gguf

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run qwen2.5-coder-7b-instruct-gguf
🤗 HF Download
huggingface-cli download worthdoing/qwen2.5-coder-7b-instruct-gguf

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
39.2
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 17
Recency (R) 98
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Qwen2.5 Coder 7b Instruct Gguf: Semantic (S:50), Authority (A:0), Popularity (P:17), Recency (R:98), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
---

🚀 What's Next?

📊

Find Training Datasets

Discover datasets compatible with this model

📈

Compare Benchmarks

See how this model ranks on standard tests

⚡

Deployment Guide

Understand deployment options

Technical Deep Dive

Qwen2.5-Coder-7B-Instruct - GGUF Quantized by worthdoing

Quantized for local Mac inference (Apple Silicon / Metal) by worthdoing

About

This is a GGUF quantized version of Qwen2.5-Coder-7B-Instruct, optimized for running locally on Apple Silicon Macs with llama.cpp, Ollama, or LM Studio.

Description

Qwen's dedicated coding model. Top-tier code generation and understanding.

Available Quantizations

File Quant BPW Size Use Case
qwen2.5-coder-7b-instruct-Q4_K_M-worthdoing.gguf Q4_K_M 4.58 ~3.7 GB Recommended - Best quality/size ratio
qwen2.5-coder-7b-instruct-Q5_K_M-worthdoing.gguf Q5_K_M 5.33 ~4.3 GB Higher quality, still fast
qwen2.5-coder-7b-instruct-Q8_0-worthdoing.gguf Q8_0 7.96 ~6.5 GB Near-original quality

How to Use

With Ollama

bash 
# Create a Modelfile
cat > Modelfile <<'MODELEOF'
FROM ./qwen2.5-coder-7b-instruct-Q4_K_M-worthdoing.gguf
MODELEOF

ollama create qwen2.5-coder-7b-instruct -f Modelfile
ollama run qwen2.5-coder-7b-instruct

With llama.cpp

bash 
llama-cli -m qwen2.5-coder-7b-instruct-Q4_K_M-worthdoing.gguf -p "Your prompt here" -ngl 99

With LM Studio

  1. Download the GGUF file
  2. Open LM Studio -> My Models -> Import
  3. Select the GGUF file and start chatting
Quant Min RAM Recommended
Q4_K_M 4 GB Mac with 8 GB+ RAM
Q5_K_M 5 GB Mac with 8 GB+ RAM
Q8_0 8 GB Mac with 12 GB+ RAM

Tags

coding, code-generation, code-review

Quantized with corelm-model pipeline by worthdoing on 2026-04-16

⚠ī¸ 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 →

📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ 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
336Downloads
Hub Discussions
🤗 Data Source: Hugging Face ↗
🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--worthdoing--qwen2.5-coder-7b-instruct-gguf
slug
worthdoing--qwen2.5-coder-7b-instruct-gguf
source
huggingface
author
worthdoing
license
Apache-2.0
tags
gguf, quantized, mac, apple-silicon, local-inference, worthdoing, text-generation, en, fr, multilingual, base_model:qwen/qwen2.5-coder-7b-instruct, license:apache-2.0, endpoints_compatible, region:us, conversational

⚙ī¸ Technical Specs

architecture
null
params billions
7
context length
4,096
pipeline tag
text-generation
vram gb
6.5
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
336
stars
0
forks
0

Data indexed from public sources. Updated daily.