---
license: apache-2.0
base_model:
- miromind-ai/MiroThinker-v1.0-8B
- nvidia/Orchestrator-8B
- rl-research/DR-Tulu-8B
- csalab/Qwen3-8B
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- miromind-ai/MiroThinker-v1.0-8B
- nvidia/Orchestrator-8B
- rl-research/DR-Tulu-8B
- csalab/Qwen3-8B
---

# HeresyAgent-8B

HeresyAgent-8B is a Mixture of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [miromind-ai/MiroThinker-v1.0-8B](https://huggingface.co/miromind-ai/MiroThinker-v1.0-8B)
* [nvidia/Orchestrator-8B](https://huggingface.co/nvidia/Orchestrator-8B)
* [rl-research/DR-Tulu-8B](https://huggingface.co/rl-research/DR-Tulu-8B)
* [csalab/Qwen3-8B](https://huggingface.co/csalab/Qwen3-8B)

## 🧩 Configuration

```yaml
slices:
  - sources:
      - model: miromind-ai/MiroThinker-v1.0-8B
        layer_range: [0, 32]
      - model: nvidia/Orchestrator-8B
        layer_range: [0, 32]
      - model: rl-research/DR-Tulu-8B
        layer_range: [0, 32]
      - model: csalab/Qwen3-8B
        layer_range: [0, 32]
base_model: miromind-ai/MiroThinker-v1.0-8B
experts:
  - source_model: miromind-ai/MiroThinker-v1.0-8B
    weight: 0.25
  - source_model: nvidia/Orchestrator-8B
    weight: 0.25
  - source_model: rl-research/DR-Tulu-8B
    weight: 0.25
  - source_model: csalab/Qwen3-8B
    weight: 0.25
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
merge_type: slerp
dtype: bfloat16
layer_range: [0, 32]
```

## 💻 Usage

```python
!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "jsuheb/HeresyAgent-8B"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)

messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```

## < === Cautions === >

# Source Specification
This model includes heretic github repo while created with using MergeKit.

# Risk Warning
This model incorporates an uncensored model with safety filters intentionally removed. It may generate harmful, biased, or illegal content.

# Intended Use Limitation
This model is provided solely for AI safety research and the exploration of ethical boundaries. Using this model with malicious purposes is strictly prohibited.

# Liability Disclaimer
All legal and ethical responsibility arising from the use of this model rests entirely with the user.