---
license: apache-2.0
base_model:
- Stormtrooperaim/Mystral-Uncensored-RP-7B
- DarkArtsForge/Avnas-7B-v1.1
- mistralai/Mistral-7B-v0.3
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- Stormtrooperaim/Mystral-Uncensored-RP-7B
- DarkArtsForge/Avnas-7B-v1.1
- mistralai/Mistral-7B-v0.3
---

 # <span style="color: red;">Shadowforge-</span> <span style="color: indigo;">3x7B-MoE</span>

Shadowforge-3x7B-MoE is a Mixture of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Stormtrooperaim/Mystral-Uncensored-RP-7B](https://huggingface.co/Stormtrooperaim/Mystral-Uncensored-RP-7B)
* [DarkArtsForge/Avnas-7B-v1.1](https://huggingface.co/DarkArtsForge/Avnas-7B-v1.1)
* [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3)


![image](https://cdn-uploads.huggingface.co/production/uploads/684648a88d895eb5ecb537ae/5qCmMU_X6h9JBEl9ga3Op.png)


## This is an UNCENSORED model with NO content restrictions. Users assume ALL RESPONSIBILITY for generated content. Not recommended for production environments or sensitive applications.

# use_cases:

* Creative fiction writing without boundaries
* Unrestricted roleplay scenarios
* Exploring controversial topics
* Dark narrative generation
* Taboo subject analysis
* Unfiltered problem solving

## 💻 Usage

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

from transformers import AutoTokenizer
import transformers
import torch

model = "Stormtrooperaim/Shadowforge-3x7B-MoE"

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"])
```