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Model: sunkencity/Llama-3.1-8B-Blasphemer-GGUF
Source: Original Platform

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README.md

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+---
+base_model: meta-llama/Llama-3.1-8B-Instruct
+tags:
+- llama-3.1
+- gguf
+- abliteration
+- uncensored
+- blasphemer
+license: llama3.1
+language:
+- en
+pipeline_tag: text-generation
+---
+
+# Llama 3.1 8B Instruct - Blasphemer (GGUF)
+
+This is an uncensored version of Meta's Llama 3.1 8B Instruct, processed using [Blasphemer](https://github.com/sunkencity999/blasphemer). This model will now deliver
+Fully uncensored outputs. Make adjustments to temperature as necessary for your own use-case. It has an extremely low refusal rate; just one follow-up is often enough
+to break refusal and receive previously censored output when a refusal Does appear. 
+
+In testing I found this model to function best at .7+ temperature for tool-calling. 
+
+
+## Model Details
+
+- **Base Model**: meta-llama/Llama-3.1-8B-Instruct
+- **Method**: Abliteration (refusal direction removal)
+- **Format**: GGUF (for llama.cpp, LM Studio, etc.)
+- **Quality Metrics**:
+  - Refusals: 3/100 (3%) ⭐ Excellent
+  - KL Divergence: 0.06 ⭐ Excellent
+  - Trial: #168 of 200
+
+## Quantization Versions
+
+| File | Size | Use Case |
+|------|------|----------|
+| Q4_K_M | ~4.5GB | Best balance - most popular |
+| Q5_K_M | ~5.5GB | Higher quality, slightly larger |
+| F16 | ~15GB | Full precision (for further quantization) |
+
+## Usage
+
+### LM Studio
+
+1. Download the GGUF file
+2. Open LM Studio
+3. Click "Import Model"
+4. Select the downloaded file
+5. Start chatting!
+
+### llama.cpp
+
+```bash
+./llama-cli -m Llama-3.1-8B-Blasphemer-Q4_K_M.gguf -p "Your prompt here"
+```
+
+### Python (llama-cpp-python)
+
+```python
+from llama_cpp import Llama
+
+llm = Llama(
+    model_path="Llama-3.1-8B-Blasphemer-Q4_K_M.gguf",
+    n_ctx=8192,
+    n_gpu_layers=-1  # Use GPU
+)
+
+response = llm("Your prompt here", max_tokens=512)
+print(response['choices'][0]['text'])
+```
+
+## What is Abliteration?
+
+Abliteration removes refusal behavior from language models by identifying and removing the neural directions responsible for safety alignment. This is done through:
+
+1. Calculating refusal directions from harmful/harmless prompt pairs
+2. Using Bayesian optimization (TPE) to find optimal removal parameters
+3. Orthogonalizing model weights to these directions
+
+The result is a model that maintains capabilities while removing refusal behavior.
+
+## Ethical Considerations
+
+This model has massively reduced safety guardrails. Users are responsible for:
+- Ensuring ethical use of the model
+- Compliance with applicable laws and regulations
+- Understanding the implications of reduced safety filtering
+
+## Performance
+
+Compared to the original Llama 3.1 8B Instruct:
+- Follows instructions more directly
+- Responds to previously refused queries
+- Maintains general capabilities (KL divergence: 0.06)
+- Greatly Reduced safety filtering
+
+## Credits
+
+- **Base Model**: Meta AI (Llama 3.1)
+- **Abliteration Tool**: [Blasphemer](https://github.com/sunkencity999/blasphemer) by Christopher Bradford
+- **Method**: Based on "Refusal in Language Models Is Mediated by a Single Direction" (Arditi et al., 2024)
+
+## Citation
+
+If you use this model, please cite:
+
+```bibtex
+@software{blasphemer2024,
+  author = {Bradford, Christopher},
+  title = {Blasphemer: Abliteration for Language Models},
+  year = {2024},
+  url = {https://github.com/sunkencity999/blasphemer}
+}
+
+@article{arditi2024refusal,
+  title={Refusal in Language Models Is Mediated by a Single Direction},
+  author={Arditi, Andy and Obmann, Oscar and Syed, Aaquib and others},
+  journal={arXiv preprint arXiv:2406.11717},
+  year={2024}
+}
+```
+
+## License
+
+This model inherits the Llama 3.1 license from Meta AI. Please review the [Llama 3.1 License](https://ai.meta.com/llama/license/) for usage terms.