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base_model: DrRiceIO7/HereticFT-Aggressive
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library_name: transformers
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tags:
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- gemma3
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- auto-antislop
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- peft
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- merge
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- fine-tuned
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- open-r1
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- mixture-of-thoughts
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license: apache-2.0
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datasets:
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- open-r1/Mixture-of-Thoughts
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---
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base_model: DrRiceIO7/HereticFT-Aggressive
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library_name: transformers
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tags:
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- gemma3
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- auto-antislop
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- peft
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- merge
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- fine-tuned
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- open-r1
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- mixture-of-thoughts
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license: apache-2.0
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datasets:
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- open-r1/Mixture-of-Thoughts
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pipeline_tag: text-generation
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---
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# HereticAggressive-CoT
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**HereticAggressive-CoT** is a merged model based on [DrRiceIO7/HereticFT-Aggressive](https://huggingface.co/DrRiceIO7/HereticFT-Aggressive).
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## ⚠️ Warning: Automated Release
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**This is an automated release.** This model has been fine-tuned and merged automatically. It has **not** been manually tested for quality, coherence, or safety. Use with caution.
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## 🚀 Overview
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This model maintains the aggressive and direct personality of the base model while incorporating fine-tuning on the [open-r1/Mixture-of-Thoughts](https://huggingface.co/datasets/open-r1/Mixture-of-Thoughts) dataset. It aims to improve reasoning capabilities (Chain of Thought) while retaining the "Heretic" style.
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## 🧪 Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "DrRiceIO7/HereticAggressive-CoT"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")
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prompt = "Explain the flaws of modern bureaucracy with aggressive detail."
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inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
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outputs = model.generate(**inputs, max_new_tokens=512)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## 🤝 Acknowledgments
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- **Base Model:** [DrRiceIO7/HereticFT-Aggressive](https://huggingface.co/DrRiceIO7/HereticFT-Aggressive)
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- **Dataset:** [open-r1/Mixture-of-Thoughts](https://huggingface.co/datasets/open-r1/Mixture-of-Thoughts)
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---
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*Disclaimer: This README was generated by Gemini 3 Flash Preview.*
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