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---
license: apache-2.0
tags:
- merge
- model_stock
- DarkStock
- Aspire
- Storm
- Llama3
- DarkEnigma
- instruction-following
- creative-writing
- coding
- roleplaying
- long-form-generation
- research
- bfloat16
base_model:
- rityak/L3.1-DarkStock-8B
- DreadPoor/Aspire-8B-model_stock
- akjindal53244/Llama-3.1-Storm-8B
- agentlans/Llama3.1-Dark-Enigma
library_name: transformers
language:
- en
datasets:
- openbuddy/openbuddy-llama3.1-8b-v22.2-131k
- THUDM/LongWriter-llama3.1-8b
- aifeifei798/DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored
pipeline_tag: text-generation
---
[](https://hf.co/QuantFactory)
# QuantFactory/Llama3.1-DarkStorm-Aspire-8B-GGUF
This is quantized version of [ZeroXClem/Llama3.1-DarkStorm-Aspire-8B](https://huggingface.co/ZeroXClem/Llama3.1-DarkStorm-Aspire-8B) created using llama.cpp
# Original Model Card
# 🌩️ **Llama3.1-DarkStorm-Aspire-8B** 🌟
Welcome to **Llama3.1-DarkStorm-Aspire-8B** — an advanced and versatile **8B parameter** AI model born from the fusion of powerful language models, designed to deliver superior performance across research, writing, coding, and creative tasks. This unique merge blends the best qualities of the **Dark Enigma**, **Storm**, and **Aspire** models, while built on the strong foundation of **DarkStock**. With balanced integration, it excels in generating coherent, context-aware, and imaginative outputs.
## 🚀 **Model Overview**
**Llama3.1-DarkStorm-Aspire-8B** combines cutting-edge natural language processing capabilities to perform exceptionally well in a wide variety of tasks:
- **Research and Analysis**: Perfect for analyzing textual data, planning experiments, and brainstorming complex ideas.
- **Creative Writing and Roleplaying**: Excels in creative writing, immersive storytelling, and generating roleplaying scenarios.
- **General AI Applications**: Use it for any application where advanced reasoning, instruction-following, and creativity are needed.
---
## 🧬 **Model Family**
This merge incorporates the finest elements of the following models:
- **[Llama3.1-Dark-Enigma](https://huggingface.co/agentlans/Llama3.1-Dark-Enigma)**: Known for its versatility across creative, research, and coding tasks. Specializes in role-playing and simulating scenarios.
- **[Llama-3.1-Storm-8B](https://huggingface.co/akjindal53244/Llama-3.1-Storm-8B)**: A finely-tuned model for structured reasoning, enhanced conversational capabilities, and agentic tasks.
- **[Aspire-8B](https://huggingface.co/DreadPoor/Aspire-8B-model_stock)**: Renowned for high-quality generation across creative and technical domains.
- **[L3.1-DarkStock-8B](https://huggingface.co/rityak/L3.1-DarkStock-8B)**: The base model providing a sturdy and balanced core of instruction-following and narrative generation.
---
## ⚙️ **Merge Details**
This model was created using the **Model Stock merge method**, meticulously balancing each component model's unique strengths. The **TIES merge** method was used to blend the layers, ensuring smooth integration across the self-attention and MLP layers for optimal performance.
### **Merge Configuration**:
```yaml
base_model: rityak/L3.1-DarkStock-8B
dtype: bfloat16
merge_method: ties
models:
- model: agentlans/Llama3.1-Dark-Enigma
parameters:
density: 0.5
weight: 0.4
- model: akjindal53244/Llama-3.1-Storm-8B
parameters:
density: 0.5
weight: 0.3
- model: DreadPoor/Aspire-8B-model_stock
parameters:
density: 0.5
weight: 0.2
- model: rityak/L3.1-DarkStock-8B
parameters:
density: 0.5
weight: 0.1
out_dtype: float16
```
The **TIES method** ensures seamless blending of each model’s specializations, allowing for smooth interpolation across their capabilities. The model uses **bfloat16** for efficient processing and **float16** for the final output, ensuring optimal performance without sacrificing precision.
---
## 🌟 **Key Features**
1. **Instruction Following & Reasoning**: Leveraging **DarkStock**'s structured capabilities, this model excels in handling complex reasoning tasks and providing precise instruction-based outputs.
2. **Creative Writing & Role-Playing**: The combination of **Aspire** and **Dark Enigma** offers powerful storytelling and roleplaying support, making it an ideal tool for immersive worlds and character-driven narratives.
3. **High-Quality Output**: The model is designed to provide coherent, context-aware responses, ensuring high-quality results across all tasks, whether it’s a research task, creative writing, or coding assistance.
---
## 📊 **Model Use Cases**
**Llama3.1-DarkStorm-Aspire-8B** is suitable for a wide range of applications:
- **Creative Writing & Storytelling**: Generate immersive stories, role-playing scenarios, or fantasy world-building with ease.
- **Technical Writing & Research**: Analyze text data, draft research papers, or brainstorm ideas with structured reasoning.
- - **Conversational AI**: Use this model to simulate engaging and contextually aware conversations.
---
## 📝 **Training Data**
The models included in this merge were each trained on diverse datasets:
- **Llama3.1-Dark-Enigma** and **Storm-8B** were trained on a mix of high-quality, public datasets, with a focus on creative and technical content.
- **Aspire-8B** emphasizes a balance between creative writing and technical precision, making it a versatile addition to the merge.
- **DarkStock** provided a stable base, finely tuned for instruction-following and diverse general applications.
---
## ⚠️ **Limitations & Responsible AI Use**
As with any AI model, it’s important to understand and consider the limitations of **Llama3.1-DarkStorm-Aspire-8B**:
- **Bias**: While the model has been trained on diverse data, biases in the training data may influence its output. Users should critically evaluate the model’s responses in sensitive scenarios.
- **Fact-based Tasks**: For fact-checking and knowledge-driven tasks, it may require careful prompting to avoid hallucinations or inaccuracies.
- **Sensitive Content**: This model is designed with an uncensored approach, so be cautious when dealing with potentially sensitive or offensive content.
---
## 🛠️ **How to Use**
You can load the model using Hugging Face's transformers library:
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "your-model-id"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="bfloat16")
prompt = "Explain the importance of data privacy in AI development."
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
For best results, use the model with the **bfloat16** precision for high efficiency, or **float16** for the final outputs.
---
## 📜 **License**
This model is open-sourced under the **Apache 2.0 License**, allowing free use, distribution, and modification with proper attribution.
---
## 💡 **Get Involved**
We’re excited to see how the community uses **Llama3.1-DarkStorm-Aspire-8B** in various creative and technical applications. Be sure to share your feedback and improvements with us on the Hugging Face model page!
---
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