← back to catalog · registered 2026-08-22 13:56

BlossomsAI/Qwen2.5-Coder-7B-Instruct-Uncensored-GGUF

BlossomsAI Qwen 7B GGUF second-order 33K ctx
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/BlossomsAI%2FQwen2.5-Coder-7B-Instruct-Uncensored-GGUF"
Response includes
  • classification m-uncensored
  • files 10
  • hub_downloads_all_time 56,729
  • author_summary 12 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
57K
17K last 30d - stable
Likes
23
Model age
21mo ago
created 2024-12-26
Downloads over time
Now60.9K→from119↑51,042%
022.3K44.6K66.9K119 on Dec 25, 202460.9K on Oct 11Dec '24Mar '25Jun '25Sep '25Dec '25MarJunSep
Dec 25, 2024 → Oct 11 · 135 snapshots · spans 655 days

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Variants by this author 2 formats · 18K downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

License
mit
Languages
en
Tags
gguf code chat uncensored en base_model:BlossomsAI/Qwen2.5-Coder-7B-Instruct-Uncensored base_model:quantized:BlossomsAI/Qwen2.5-Coder-7B-Instruct-Uncensored license:mit endpoints_compatible region:us conversational

Related

Total size
38.3 GB
Files
10
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-02-11 11:32

Files by quantization

Auxiliary files 10 files 38.3 GB
q8_0.gguf 7.54 GB c508d6de download
q6_k.gguf 5.82 GB 943adfcf download
q5_k_m.gguf 5.07 GB ebc5b013 download
q5_k_s.gguf 4.95 GB 1367aad0 download
q4_k_m.gguf 4.36 GB e6b94e07 download
q4_k_s.gguf 4.15 GB 6b3d0058 download
q3_k_m.gguf 3.55 GB 5d4123f9 download
q2_k.gguf 2.81 GB ddc0a6e3 download
README.md 2.23 KB 5042a636 download
.gitattributes 1.85 KB ce5e3034 download

README current version from Hugging Face


license: mit
language:

  • en
    base_model:
  • BlossomsAI/Qwen2.5-Coder-7B-Instruct-Uncensored
    tags:
  • code
  • chat
  • uncensored

Logo

🚀 Qwen2.5-Coder-7B-Instruct-Uncensored-GGUF

Optimized quantized models for efficient inference

📋 Overview

A collection of optimized GGUF quantized models derived from BlossomsAI/Qwen2.5-Coder-7B-Instruct-Uncensored, providing various performance-quality tradeoffs.

💎 Model Variants

Variant Use Case Download
Q2_K Basic text completion tasks 📥
Q3_K_M Memory-efficient quality operations 📥
Q4_K_S Balanced performance and quality 📥
Q4_K_M Balanced performance and quality 📥
Q5_K_S Enhanced quality text generation 📥
Q5_K_M Enhanced quality text generation 📥
Q6_K Superior quality outputs 📥
Q8_0 Maximum quality, production-grade results 📥

🤝 Contributors

Developed with ❤️ by BlossomAI


Star ⭐️ this repo if you find it valuable!

README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

  1. 2025-02-11Create README.mdeb151722.2 KB
    Loading...

Discussions 1 thread

  1. 2025-01-17sir, you can create the gguf of qwen2.5-coder-14b Uncensoredopen3 💬#1
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration