mariaboukhelfa/intent_catgory_model
The mariaboukhelfa/intent_catgory_model is an 8 billion parameter Llama-3-based instruction-tuned language model developed by mariaboukhelfa. Finetuned from unsloth/llama-3-8b-Instruct-bnb-4bit, this model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for intent categorization tasks, leveraging its Llama-3 architecture for efficient and accurate classification.
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Model Overview
The mariaboukhelfa/intent_catgory_model is an 8 billion parameter language model, finetuned by mariaboukhelfa. It is based on the Llama-3 architecture, specifically building upon the unsloth/llama-3-8b-Instruct-bnb-4bit model.
Key Characteristics
- Architecture: Llama-3-based, leveraging the
llama-3-8b-Instructfoundation. - Training Efficiency: This model was finetuned with Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
- License: Distributed under the Apache-2.0 license, allowing for broad use and modification.
Intended Use Cases
This model is specifically designed and finetuned for intent categorization tasks. Its Llama-3 foundation, combined with specialized finetuning, makes it suitable for applications requiring the classification of user intents from text inputs. Developers can integrate this model for efficient and accurate intent recognition in various NLP applications.