---
license: other
license_name: hugston-licenced
license_link: LICENSE
---
This is an Abliterated version of LMF2.5-350M using a modified version of Prometheus, then using Quanta and HugstonOne.


The aim is to understand the safety mechanism of different llm models for research purposes. 

Here we show proof of concept of how we can change the model behaviour preserving accuracy and lowering the refusal rate
with very few trial which run in relatively small datasets. 
As a matter of fact it can run in a cheap laptop in cpu narrowing it down to 5-20 min for a small model. 

6 trials Refusals: 10/1000, KL divergence: 0.2577 

---

# Credit to LiquidAI for the model creation
# Credit to https://huggingface.co/wangzhang for abliteration method
# Credit to LLama.cpp team for the great contribution
# Credit to Hugston Team for Abliteration, Converting, Quantizing, Testing, Benching and other...
# Credit to Huggingface for the amazing hosting platform

---

# Keep away from children

Here we show the behaviour running the model in HugstonOne (the 0.8b, as an example).
![image](https://cdn-uploads.huggingface.co/production/uploads/6818be9259cb758d06603579/PA04KgI357zs0JrqsnDeT.png)

The quantization in GGUF was made in f32 for beter quants.  
Here we show Quanta our convertor and Quantizer tool. 

![image](https://cdn-uploads.huggingface.co/production/uploads/6818be9259cb758d06603579/wmfqVJ6TtAmTIFtmnh12y.png)