abhirajs005/llama3-cardio-fhir-v1
The abhirajs005/llama3-cardio-fhir-v1 is an 8 billion parameter Llama 3 model, fine-tuned by abhirajs005 from unsloth/llama-3-8b-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library for accelerated fine-tuning. It is specifically optimized for applications requiring a Llama 3 architecture with 8192 tokens context length, offering enhanced performance for its specialized domain.
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Model Overview
The abhirajs005/llama3-cardio-fhir-v1 is an 8 billion parameter Llama 3 model, fine-tuned by abhirajs005. It is based on the unsloth/llama-3-8b-bnb-4bit base model and utilizes the Unsloth library in conjunction with Huggingface's TRL library for efficient and accelerated training.
Key Characteristics
- Architecture: Llama 3 family.
- Parameter Count: 8 billion parameters.
- Base Model: Fine-tuned from
unsloth/llama-3-8b-bnb-4bit. - Training Efficiency: Leverages Unsloth for 2x faster fine-tuning.
- Context Length: Supports an 8192-token context window.
Intended Use Cases
This model is suitable for applications that benefit from a Llama 3 architecture with an 8B parameter count and optimized training. Its fine-tuning process suggests potential specialization, making it a strong candidate for tasks where the base Llama 3 capabilities are enhanced by the specific fine-tuning data (though the specific domain is not detailed in the provided README). Developers looking for an efficiently trained Llama 3 variant should consider this model.