mukesh12s/leo-intent-v1
The mukesh12s/leo-intent-v1 is an 8 billion parameter Llama 3.1 instruction-tuned causal language model developed by mukesh12s. Fine-tuned from unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit, this model leverages Unsloth for accelerated training. It is designed for general instruction-following tasks, benefiting from the Llama 3.1 architecture and efficient fine-tuning methods.
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Model Overview
The mukesh12s/leo-intent-v1 is an 8 billion parameter instruction-tuned language model, developed by mukesh12s. It is fine-tuned from the unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit base model, indicating its foundation in the Llama 3.1 architecture.
Key Characteristics
- Base Model: Fine-tuned from
meta-llama-3.1-8b-instruct. - Parameter Count: 8 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: The model was trained using Unsloth, a library known for accelerating the fine-tuning process of large language models by up to 2x.
Potential Use Cases
Given its instruction-tuned nature and Llama 3.1 foundation, this model is suitable for a variety of natural language processing tasks, including:
- Instruction Following: Responding to user prompts and executing specific commands.
- Text Generation: Creating coherent and contextually relevant text.
- Chatbots and Conversational AI: Engaging in dialogue and providing informative responses.
Licensing
The model is released under the Apache 2.0 license, allowing for broad use and distribution.