abhi9ab/DeepSeek-R1-Distill-Llama-8B-finance-v1
The abhi9ab/DeepSeek-R1-Distill-Llama-8B-finance-v1 is an 8 billion parameter Llama-based language model, fine-tuned by abhi9ab using LoRA for specialized financial tasks. This model leverages a distilled DeepSeek-R1 base and was optimized with Unsloth for efficient training. It is specifically designed to enhance performance in financial question answering, generation, and instruction-following, making it suitable for domain-specific financial applications.
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Model Overview
This model, abhi9ab/DeepSeek-R1-Distill-Llama-8B-finance-v1, is an 8 billion parameter language model developed by abhi9ab. It is a fine-tuned version of the unsloth/DeepSeek-R1-Distill-Llama-8B base model, optimized for financial applications. The fine-tuning process utilized LoRA (Low-Rank Adaptation) for efficient training, leveraging the Unsloth library to accelerate the process by 2x.
Key Capabilities
- Financial Domain Specialization: Enhanced performance on tasks requiring domain-specific knowledge in finance.
- Instruction Following: Designed for financial question answering, generation, and instruction-based tasks.
- Efficient Fine-Tuning: Developed using LoRA, allowing for effective adaptation with reduced computational resources.
- Dataset: Fine-tuned on a 5,000-entry subset of the Josephgflowers/Finance-Instruct-500k dataset.
Intended Use Cases
This model is ideal for:
- Financial Question Answering: Providing accurate responses to finance-related queries.
- Financial Text Generation: Generating content relevant to the financial sector.
- Instruction-based Financial Tasks: Executing instructions that require understanding and application of financial concepts.
- Natural Language Understanding (NLU): General NLU tasks that can benefit from a finance-specific fine-tuning.