--- license: apache-2.0 tags: - merge - mergekit - lazymergekit - bfloat16 - text-generation-inference - model_stock - crypto - finance - llama language: - en base_model: - Chainbase-Labs/Theia-Llama-3.1-8B-v1 - EpistemeAI/Fireball-Meta-Llama-3.2-8B-Instruct-agent-003-128k-code-DPO - mukaj/Llama-3.1-Hawkish-8B pipeline_tag: text-generation library_name: transformers --- # ZeroXClem/LLama3.1-Hawkish-Theia-Fireball-8B **ZeroXClem/LLama3.1-Hawkish-Theia-Fireball-8B** is an advanced language model meticulously crafted by merging three pre-trained models using the powerful [mergekit](https://github.com/cg123/mergekit) framework. This fusion leverages the **Model Stock** merge method to combine the specialized capabilities of **Theia-Llama**, **Fireball-Meta-Llama**, and **Llama-Hawkish**. The resulting model excels in creative text generation, technical instruction following, financial reasoning, and dynamic conversational interactions. ## 🚀 Merged Models This model merge incorporates the following: - [**Chainbase-Labs/Theia-Llama-3.1-8B-v1**](https://huggingface.co/Chainbase-Labs/Theia-Llama-3.1-8B-v1): Specializes in cryptocurrency-oriented knowledge, enhancing the model's ability to generate and comprehend crypto-related content with high accuracy and depth. - [**EpistemeAI/Fireball-Meta-Llama-3.2-8B-Instruct-agent-003-128k-code-DPO**](https://huggingface.co/EpistemeAI/Fireball-Meta-Llama-3.2-8B-Instruct-agent-003-128k-code-DPO): Focuses on instruction-following and coding capabilities, improving the model's performance in understanding and executing user commands, as well as generating executable code snippets. - [**mukaj/Llama-3.1-Hawkish-8B**](https://huggingface.co/mukaj/Llama-3.1-Hawkish-8B): Enhances financial reasoning and mathematical precision, enabling the model to handle complex financial analyses, economic discussions, and quantitative problem-solving with high proficiency. ## 🧩 Merge Configuration The configuration below outlines how the models are merged using the **Model Stock** method. This approach ensures a balanced and effective integration of the unique strengths from each source model. ```yaml # Merge configuration for ZeroXClem/LLama3.1-Hawkish-Theia-Fireball-8B using Model Stock models: - model: Chainbase-Labs/Theia-Llama-3.1-8B-v1 - model: EpistemeAI/Fireball-Meta-Llama-3.2-8B-Instruct-agent-003-128k-code-DPO - model: mukaj/Llama-3.1-Hawkish-8B merge_method: model_stock base_model: mukaj/Llama-3.1-Hawkish-8B normalize: false int8_mask: true dtype: bfloat16 ``` ### Key Parameters - **Merge Method (`merge_method`):** Utilizes the **Model Stock** method, as described in [Model Stock](https://arxiv.org/abs/2403.19522), to effectively combine multiple models by leveraging their strengths. - **Models (`models`):** Specifies the list of models to be merged: - **Chainbase-Labs/Theia-Llama-3.1-8B-v1:** Enhances cryptocurrency-oriented knowledge and content generation. - **EpistemeAI/Fireball-Meta-Llama-3.2-8B-Instruct-agent-003-128k-code-DPO:** Improves instruction-following and coding capabilities. - **mukaj/Llama-3.1-Hawkish-8B:** Enhances financial reasoning and mathematical precision. - **Base Model (`base_model`):** Defines the foundational model for the merge, which is **mukaj/Llama-3.1-Hawkish-8B** in this case. - **Normalization (`normalize`):** Set to `false` to retain the original scaling of the model weights during the merge. - **INT8 Mask (`int8_mask`):** Enabled (`true`) to apply INT8 quantization masking, optimizing the model for efficient inference without significant loss in precision. - **Data Type (`dtype`):** Uses `bfloat16` to maintain computational efficiency while ensuring high precision. ## 🏆 Performance Highlights - **Cryptocurrency Knowledge:** Enhanced ability to generate and comprehend crypto-related content, making the model highly effective for blockchain discussions, crypto market analysis, and related queries. - **Instruction Following and Coding:** Improved performance in understanding and executing user instructions, as well as generating accurate and executable code snippets, suitable for coding assistance and technical support. - **Financial Reasoning and Mathematical Precision:** Advanced capabilities in handling complex financial analyses, economic discussions, and quantitative problem-solving, making the model ideal for financial modeling, investment analysis, and educational purposes. - **Smooth Weight Blending:** Utilization of the Model Stock method ensures a harmonious integration of different model attributes, resulting in balanced performance across various specialized tasks. - **Optimized Inference:** INT8 masking and `bfloat16` data type contribute to efficient computation, enabling faster response times without compromising quality. ## 🎯 Use Case & Applications **ZeroXClem/LLama3.1-Hawkish-Theia-Fireball-8B** is designed to excel in environments that demand a combination of creative generation, technical instruction following, financial reasoning, and dynamic conversational interactions. Ideal applications include: - **Cryptocurrency Analysis and Reporting:** Generating detailed reports, analyses, and summaries related to blockchain projects, crypto markets, and financial technologies. - **Coding Assistance and Technical Support:** Providing accurate and executable code snippets, debugging assistance, and technical explanations for developers and technical professionals. - **Financial Modeling and Investment Analysis:** Assisting financial analysts and investors in creating models, performing economic analyses, and making informed investment decisions through precise calculations and reasoning. - **Educational Tools and Tutoring Systems:** Offering detailed explanations, answering complex questions, and assisting in educational content creation across subjects like finance, economics, and mathematics. - **Interactive Conversational Agents:** Powering chatbots and virtual assistants with specialized knowledge in cryptocurrency, finance, and technical domains, enhancing user interactions and support. - **Content Generation for Finance and Tech Blogs:** Creating high-quality, contextually relevant content for blogs, articles, and marketing materials focused on finance, technology, and cryptocurrency. ## 📝 Usage To utilize **ZeroXClem/LLama3.1-Hawkish-Theia-Fireball-8B**, follow the steps below: ### Installation First, install the necessary libraries: ```bash pip install -qU transformers accelerate ``` ### Example Code Below is an example of how to load and use the model for text generation: ```python from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline import torch # Define the model name model_name = "ZeroXClem/LLama3.1-Hawkish-Theia-Fireball-8B" # Load the tokenizer tokenizer = AutoTokenizer.from_pretrained(model_name) # Load the model model = AutoModelForCausalLM.from_pretrained( model_name, torch_dtype=torch.bfloat16, device_map="auto" ) # Initialize the pipeline text_generator = pipeline( "text-generation", model=model, tokenizer=tokenizer, torch_dtype=torch.bfloat16, device_map="auto" ) # Define the input prompt prompt = "Explain the impact of decentralized finance on traditional banking systems." # Generate the output outputs = text_generator( prompt, max_new_tokens=150, do_sample=True, temperature=0.7, top_k=50, top_p=0.95 ) # Print the generated text print(outputs[0]["generated_text"]) ``` ### Notes - **Fine-Tuning:** This merged model may require fine-tuning to optimize performance for specific applications or domains, especially in highly specialized fields like cryptocurrency and finance. - **Resource Requirements:** Ensure that your environment has sufficient computational resources, especially GPU-enabled hardware, to handle the model efficiently during inference. - **Customization:** Users can adjust parameters such as `temperature`, `top_k`, and `top_p` to control the creativity and diversity of the generated text, tailoring the model's output to specific needs. ## 📜 License This model is open-sourced under the **Apache-2.0 License**. ## 💡 Tags - `merge` - `mergekit` - `model_stock` - `Llama` - `Hawkish` - `Theia` - `Fireball` - `ZeroXClem/LLama3.1-Hawkish-Theia-Fireball-8B` - `Chainbase-Labs/Theia-Llama-3.1-8B-v1` - `EpistemeAI/Fireball-Meta-Llama-3.2-8B-Instruct-agent-003-128k-code-DPO` - `mukaj/Llama-3.1-Hawkish-8B`