🧠
Qwen2.5 7b Sft Capybara Gguf model by ermiaazarkhalili
⭐ 36.2
🧠
Model

Qwen2.5 7b Sft Capybara Gguf

by ermiaazarkhalili hf-model--ermiaazarkhalili--qwen2.5-7b-sft-capybara-gguf
Nexus Index
36.2 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 10
R: Recency 98
Q: Quality 30
Tech Context
7 Params
4.096K Ctx
Vital Performance
127 DL / 30D
0.0%
Source →
Audited 36.2 FNI Score
7B Params
4k Context
127 Downloads
8G GPU ~7GB Est. VRAM
Restricted CC License
Model Information Summary
Entity Passport
Registry ID hf-model--ermiaazarkhalili--qwen2.5-7b-sft-capybara-gguf
License CC-BY-NC-4.0
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__ermiaazarkhalili__qwen2.5_7b_sft_capybara_gguf,
  author = {ermiaazarkhalili},
  title = {Qwen2.5 7b Sft Capybara Gguf Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/ermiaazarkhalili/qwen2.5-7b-sft-capybara-gguf}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
ermiaazarkhalili. (2026). Qwen2.5 7b Sft Capybara Gguf [Model]. Free2AITools. https://huggingface.co/ermiaazarkhalili/qwen2.5-7b-sft-capybara-gguf

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run qwen2.5-7b-sft-capybara-gguf
🤗 HF Download
huggingface-cli download ermiaazarkhalili/qwen2.5-7b-sft-capybara-gguf

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
36.2
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 10
Recency (R) 98
Quality (Q) 30

đŸ’Ŧ Index Insight

FNI V2.0 for Qwen2.5 7b Sft Capybara Gguf: Semantic (S:50), Authority (A:0), Popularity (P:10), Recency (R:98), Quality (Q:30).

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

Qwen2.5-7B-SFT-Capybara-GGUF

GGUF quantized versions of ermiaazarkhalili/Qwen2.5-7B-SFT-Capybara for use with llama.cpp, Ollama, LM Studio, and other GGUF-compatible tools.

Available Quantizations

File Quantization Quality Use Case
qwen2.5-7b-sft-capybara-q4_k_m.gguf Q4_K_M Good Recommended - Best balance of quality and size
qwen2.5-7b-sft-capybara-q5_k_m.gguf Q5_K_M Better Higher quality, moderate size increase
qwen2.5-7b-sft-capybara-q8_0.gguf Q8_0 Best Highest quality quantization

Download Specific Quantization

Using huggingface-cli

bash 
# Download Q4_K_M (recommended)
huggingface-cli download ermiaazarkhalili/Qwen2.5-7B-SFT-Capybara-GGUF qwen2.5-7b-sft-capybara-q4_k_m.gguf --local-dir ./models

# Download Q5_K_M (higher quality)
huggingface-cli download ermiaazarkhalili/Qwen2.5-7B-SFT-Capybara-GGUF qwen2.5-7b-sft-capybara-q5_k_m.gguf --local-dir ./models

# Download Q8_0 (best quality)
huggingface-cli download ermiaazarkhalili/Qwen2.5-7B-SFT-Capybara-GGUF qwen2.5-7b-sft-capybara-q8_0.gguf --local-dir ./models

# Download all quantizations
huggingface-cli download ermiaazarkhalili/Qwen2.5-7B-SFT-Capybara-GGUF --local-dir ./models

Using wget

bash 
# Q4_K_M
wget https://huggingface.co/ermiaazarkhalili/Qwen2.5-7B-SFT-Capybara-GGUF/resolve/main/qwen2.5-7b-sft-capybara-q4_k_m.gguf

# Q5_K_M
wget https://huggingface.co/ermiaazarkhalili/Qwen2.5-7B-SFT-Capybara-GGUF/resolve/main/qwen2.5-7b-sft-capybara-q5_k_m.gguf

# Q8_0
wget https://huggingface.co/ermiaazarkhalili/Qwen2.5-7B-SFT-Capybara-GGUF/resolve/main/qwen2.5-7b-sft-capybara-q8_0.gguf

Usage

Ollama

bash 
# Pull specific quantization
ollama pull hf.co/ermiaazarkhalili/Qwen2.5-7B-SFT-Capybara-GGUF:Q4_K_M

# Or create from local file
cat > Modelfile << EOF
FROM ./qwen2.5-7b-sft-capybara-q4_k_m.gguf
EOF

ollama create qwen2.5-7b-sft-capybara -f Modelfile
ollama run qwen2.5-7b-sft-capybara

llama.cpp

bash 
# Run with llama-cli
./llama-cli -m qwen2.5-7b-sft-capybara-q4_k_m.gguf -p "Your prompt here" -n 256

# Run as server
./llama-server -m qwen2.5-7b-sft-capybara-q4_k_m.gguf --host 0.0.0.0 --port 8080

llama-cpp-python

python 
from llama_cpp import Llama

llm = Llama(
    model_path="qwen2.5-7b-sft-capybara-q4_k_m.gguf",
    n_ctx=2048,
    n_gpu_layers=-1  # Use all GPU layers
)

output = llm(
    "What is machine learning?",
    max_tokens=256,
    temperature=0.7,
)
print(output['choices'][0]['text'])

LM Studio

  1. Download the desired GGUF file from this repository
  2. Open LM Studio and navigate to the Models tab
  3. Click "Add Model" and select the downloaded GGUF file
  4. Load the model and start chatting

GPT4All

  1. Download the Q4_K_M GGUF file
  2. Open GPT4All and go to Settings > Models
  3. Add the GGUF file path
  4. Select the model and start using

Original Model

This is a quantized version of ermiaazarkhalili/Qwen2.5-7B-SFT-Capybara. See the original model card for:

  • Training details and methodology
  • Dataset information
  • Performance metrics
  • Full usage examples with Transformers

Conversion Details

Property Value
Source Model ermiaazarkhalili/Qwen2.5-7B-SFT-Capybara
Conversion Date 2026-04-09
Quantizations Q4_K_M, Q5_K_M, Q8_0
Converter llama.cpp

License

Same license as the original model. See ermiaazarkhalili/Qwen2.5-7B-SFT-Capybara for details.

Converted using the Slurm Model Trainer skill

⚠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
127Downloads
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--ermiaazarkhalili--qwen2.5-7b-sft-capybara-gguf
slug
ermiaazarkhalili--qwen2.5-7b-sft-capybara-gguf
source
huggingface
author
ermiaazarkhalili
license
CC-BY-NC-4.0
tags
gguf, llama.cpp, ollama, lm-studio, quantized, license:cc-by-nc-4.0, endpoints_compatible, region:us, conversational

⚙ī¸ Technical Specs

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

📊 Engagement & Metrics

downloads
127
stars
0
forks
0

Data indexed from public sources. Updated daily.