---
library_name: transformers
base_model:
- BoltMonkey/NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated
- BoltMonkey/DreadMix
tags:
- merge
- mergekit
- lazymergekit
- BoltMonkey/NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated
- BoltMonkey/DreadMix
pipeline_tag: text-generation
---

# SuperNeuralDreadDevil-8b

SuperNeuralDreadDevil-8b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [BoltMonkey/NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated](https://huggingface.co/BoltMonkey/NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated)
* [BoltMonkey/DreadMix](https://huggingface.co/BoltMonkey/DreadMix)

## 🧩 Configuration

```yamlmodels:
  - model: NousResearch/Meta-Llama-3.1-8B-Instruct
  - model: BoltMonkey/NeuralDaredevil-SuperNova-Lite-7B-DARETIES-abliterated
    parameters:
      density: 0.53
      weight: 0.55
  - model: BoltMonkey/DreadMix
    parameters:
      density: 0.53
      weight: 0.45
merge_method: dare_ties
base_model: NousResearch/Meta-Llama-3.1-8B-Instruct
parameters:
  int8_mask: true
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "BoltMonkey/SuperNeuralDreadDevil-8b"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

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"])
```