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Model: richardyoung/Qwen3-8B-Abliterated
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-8B
+tags:
+- abliterated
+- uncensored
+- qwen3
+library_name: transformers
+pipeline_tag: text-generation
+---
+
+# Qwen3-8B-Abliterated
+
+An abliterated version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) with reduced safety refusals.
+
+## Abliteration Details
+
+This model was created using [jim-plus/llm-abliteration](https://github.com/jim-plus/llm-abliteration):
+
+- **Base Model**: Qwen/Qwen3-8B
+- **Layers Modified**: 15-30 (middle layers where refusal behavior is encoded)
+- **Measurement Layer**: Layer 25 (highest signal quality at 0.123)
+- **Method**: Standard abliteration (directional ablation)
+- **Scale**: 1.0 (full ablation)
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model = AutoModelForCausalLM.from_pretrained(
+    "richardyoung/Qwen3-8B-Abliterated",
+    device_map="auto",
+    torch_dtype=torch.bfloat16,
+)
+tokenizer = AutoTokenizer.from_pretrained("richardyoung/Qwen3-8B-Abliterated")
+
+messages = [{"role": "user", "content": "Your prompt here"}]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+
+outputs = model.generate(**inputs, max_new_tokens=200, do_sample=True, temperature=0.7)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+```
+
+## Disclaimer
+
+This model is provided for research purposes only. The abliteration process removes certain safety guardrails. Users are responsible for ensuring ethical use of this model.
+
+## Credits
+
+- Original model: [Qwen Team](https://huggingface.co/Qwen)
+- Abliteration method: [jim-plus/llm-abliteration](https://github.com/jim-plus/llm-abliteration)
+- Abliteration theory: [Abliteration blog post](https://huggingface.co/blog/mlabonne/abliteration)