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---
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license: apache-2.0
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tags:
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- merge
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- model_stock
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- DarkStock
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- Aspire
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- Storm
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- Llama3
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- DarkEnigma
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- instruction-following
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- creative-writing
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- coding
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- roleplaying
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- long-form-generation
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- research
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- bfloat16
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base_model:
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- rityak/L3.1-DarkStock-8B
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- DreadPoor/Aspire-8B-model_stock
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- akjindal53244/Llama-3.1-Storm-8B
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- agentlans/Llama3.1-Dark-Enigma
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library_name: transformers
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language:
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- en
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datasets:
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- openbuddy/openbuddy-llama3.1-8b-v22.2-131k
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- THUDM/LongWriter-llama3.1-8b
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- aifeifei798/DarkIdol-Llama-3.1-8B-Instruct-1.2-Uncensored
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pipeline_tag: text-generation
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---
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[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
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# QuantFactory/Llama3.1-DarkStorm-Aspire-8B-GGUF
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This is quantized version of [ZeroXClem/Llama3.1-DarkStorm-Aspire-8B](https://huggingface.co/ZeroXClem/Llama3.1-DarkStorm-Aspire-8B) created using llama.cpp
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# Original Model Card
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# 🌩️ **Llama3.1-DarkStorm-Aspire-8B** 🌟
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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.
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## 🚀 **Model Overview**
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**Llama3.1-DarkStorm-Aspire-8B** combines cutting-edge natural language processing capabilities to perform exceptionally well in a wide variety of tasks:
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- **Research and Analysis**: Perfect for analyzing textual data, planning experiments, and brainstorming complex ideas.
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- **Creative Writing and Roleplaying**: Excels in creative writing, immersive storytelling, and generating roleplaying scenarios.
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- **General AI Applications**: Use it for any application where advanced reasoning, instruction-following, and creativity are needed.
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---
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## 🧬 **Model Family**
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This merge incorporates the finest elements of the following models:
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- **[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.
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- **[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.
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- **[Aspire-8B](https://huggingface.co/DreadPoor/Aspire-8B-model_stock)**: Renowned for high-quality generation across creative and technical domains.
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- **[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.
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---
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## ⚙️ **Merge Details**
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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.
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### **Merge Configuration**:
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```yaml
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base_model: rityak/L3.1-DarkStock-8B
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dtype: bfloat16
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merge_method: ties
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models:
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- model: agentlans/Llama3.1-Dark-Enigma
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parameters:
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density: 0.5
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weight: 0.4
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- model: akjindal53244/Llama-3.1-Storm-8B
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parameters:
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density: 0.5
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weight: 0.3
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- model: DreadPoor/Aspire-8B-model_stock
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parameters:
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density: 0.5
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weight: 0.2
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- model: rityak/L3.1-DarkStock-8B
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parameters:
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density: 0.5
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weight: 0.1
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out_dtype: float16
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```
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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.
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---
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## 🌟 **Key Features**
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1. **Instruction Following & Reasoning**: Leveraging **DarkStock**'s structured capabilities, this model excels in handling complex reasoning tasks and providing precise instruction-based outputs.
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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.
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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.
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---
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## 📊 **Model Use Cases**
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**Llama3.1-DarkStorm-Aspire-8B** is suitable for a wide range of applications:
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- **Creative Writing & Storytelling**: Generate immersive stories, role-playing scenarios, or fantasy world-building with ease.
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- **Technical Writing & Research**: Analyze text data, draft research papers, or brainstorm ideas with structured reasoning.
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- - **Conversational AI**: Use this model to simulate engaging and contextually aware conversations.
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---
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## 📝 **Training Data**
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The models included in this merge were each trained on diverse datasets:
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- **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.
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- **Aspire-8B** emphasizes a balance between creative writing and technical precision, making it a versatile addition to the merge.
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- **DarkStock** provided a stable base, finely tuned for instruction-following and diverse general applications.
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---
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## ⚠️ **Limitations & Responsible AI Use**
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As with any AI model, it’s important to understand and consider the limitations of **Llama3.1-DarkStorm-Aspire-8B**:
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- **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.
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- **Fact-based Tasks**: For fact-checking and knowledge-driven tasks, it may require careful prompting to avoid hallucinations or inaccuracies.
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- **Sensitive Content**: This model is designed with an uncensored approach, so be cautious when dealing with potentially sensitive or offensive content.
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---
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## 🛠️ **How to Use**
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You can load the model using Hugging Face's transformers library:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "your-model-id"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="bfloat16")
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prompt = "Explain the importance of data privacy in AI development."
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(**inputs, max_new_tokens=100)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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For best results, use the model with the **bfloat16** precision for high efficiency, or **float16** for the final outputs.
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---
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## 📜 **License**
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This model is open-sourced under the **Apache 2.0 License**, allowing free use, distribution, and modification with proper attribution.
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---
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## 💡 **Get Involved**
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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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---
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