rvncto/Qwen2.5-VL-72B-Instruct-abliterated-deep-GGUF
? Why do I need an app?
The browser can't see your hardware
For privacy reasons a browser tells us at most "≥ 8 GB RAM, 8 cores" - same reading whether you have 8 GB or 128 GB. It has no idea how much RAM is free right now, which apps are open, or whether you have a GPU.
The Abliteration app is integrated with your machine
It reads your exact RAM, GPU model and VRAM, free memory right now, and picks the sharpest quant that still fits. Every model page lights up precisely for your rig.
And you can chat with any model, right now
The app is a full local runtime - no API keys, no subscription, everything runs on your machine. Click any model on this site and start a conversation in seconds.
Get the free app →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/rvncto%2FQwen2.5-VL-72B-Instruct-abliterated-deep-GGUF" - classification m8
- files 2
- hub_downloads_all_time 1,292
- author_summary 4 models
- readme_text full
Repackaging (quantization)
Why this label 3 signals
- 'abliterated' in name/tags
- is_gguf=1
- assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
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? →Variants by this author
The same weights this author released in different packaging. Pick the format that matches your runtime.
- rvncto/Qwen2.5-VL-72B-Instruct-abliterated-deep-GGUF (this)
- rvncto/Qwen2.5-VL-72B-Instruct-abliterated-deep
Metadata
Related
Files by quantization
README
The author did not publish a README.