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TiGa-RCE/Qwen2.5-0.5B-Instruct-OBLITERATED
Qwen2.5-0.5B-Instruct-OBLITERATED is a machine learning model from TiGa-RCE. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This model was abliterated using the surgical method via OBLITERATUS.
Downloads · 30 days
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From the Hugging Face model README
This model was abliterated using the surgical method via
OBLITERATUS.
| Detail | Value |
|---|---|
| Base model | Qwen/Qwen2.5-0.5B-Instruct |
| Method | surgical |
| Source | benchmark_mm |
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("Qwen2.5-0.5B-Instruct-OBLITERATED")
tokenizer = AutoTokenizer.from_pretrained("Qwen2.5-0.5B-Instruct-OBLITERATED")
prompt = "Hello, how are you?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
OBLITERATUS is an open-source tool for removing refusal behavior from language models via activation engineering (abliteration). Learn more at github.com/elder-plinius/OBLITERATUS.