ZeroXClem/Llama3.1-BestMix-Chem-Einstein-8B
Llama3.1-BestMix-Chem-Einstein-8B is an innovative, meticulously blended model designed to excel in instruction-following, chemistry-focused tasks, and long-form conversational generation. This model fuses the best qualities of multiple Llama3-based architectures, making it highly versatile for both general and specialized tasks. π»π§ β¨
π Family Tree
This model is the result of merging the following:
- bunnycore/Best-Mix-Llama-3.1-8B: A balanced blend of top Llama models, optimized for general performance across reasoning, instruction-following, and math.
- USTC-KnowledgeComputingLab/Llama3-KALE-LM-Chem-1.5-8B: A model specialized in scientific knowledge and chemistry, excelling in chemistry benchmarks.
- Weyaxi/Einstein-v6.1-Llama3-8B: Fine-tuned for long-form generation, conversation-heavy tasks, and optimized with cutting-edge techniques for efficient memory usage and fast performance.
𧬠Model Lineage
A: bunnycore/Best-Mix-Llama-3.1-8B
- A masterful blend of several Llama3 models like Aurora_faustus, TitanFusion, and OpenMath2.
- Provides a balanced performance in a variety of tasks such as reasoning, math, and instruction-following.
- Key contributor to the overall versatility of the merged model.
B: USTC-KnowledgeComputingLab/Llama3-KALE-LM-Chem-1.5-8B
- Specializes in chemistry and scientific knowledge, outperforming many larger models in chemistry benchmarks.
- Adds scientific rigor and domain-specific expertise to the merged model, making it perfect for scientific and academic tasks.
C: Weyaxi/Einstein-v6.1-Llama3-8B
- Fine-tuned on a wide range of instructive and conversational datasets like WizardLM, Alpaca, and ShareGPT.
- Optimized for long-form text generation and enhanced with xformers attention and flash attention techniques for better performance.
- Key player in dialogue-based tasks and long conversation generation.
π οΈ Merge Details
This model was merged using the TIES merge method, ensuring a smooth integration of the key strengths from each contributing model. Here's the configuration used:
yaml
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models:
- model: bunnycore/Best-Mix-Llama-3.1-8B
parameters:
density: [1, 0.7, 0.5]
weight: 1.0
- model: USTC-KnowledgeComputingLab/Llama3-KALE-LM-Chem-1.5-8B
parameters:
density: 0.6
weight: [0.3, 0.7, 1.0]
- model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.4
weight:
- filter: mlp
value: 0.5
- filter: self_attn
value: 0.7
- value: 0.5
merge_method: ties
base_model: bunnycore/Best-Mix-Llama-3.1-8B
parameters:
normalize: true
int8_mask: true
dtype: float16
π― Key Features & Capabilities
1. Instruction Following & General Reasoning:
With the foundation of Best-Mix, this model excels in general-purpose reasoning, instruction-following, and tasks that require high adaptability.
2. Scientific & Chemistry Expertise:
Thanks to the contribution from KALE-LM-Chem, this model shines in scientific research, particularly chemistry-focused tasks, making it ideal for academic and research purposes.
3. Long-Form & Conversational Mastery:
With Einstein-v6.1, the model handles long-form generation effortlessly, excelling in extended conversations and structured dialogue applications.
π Performance Benchmarks
While still in its early stages, Llama3.1-BestMix-Chem-Einstein-8B is expected to perform well across a variety of benchmarks, including:
- Chemistry-focused benchmarks (KALE-LM-Chem)
- Instruction-following tasks (Best-Mix)
- Conversational AI and long-form text generation (Einstein-v6.1)
Further testing and evaluation will continue to refine this model's capabilities.
π License
This model is open-sourced under the Apache-2.0 License, allowing free use and modification with proper attribution.
π‘ Tags
merge
TIES
BestMix
Chemistry
Einstein
instruction-following
long-form-generation
conversational
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