deartheiz/LLM-LuatGiaoThong
LLM-LuatGiaoThong is an 8 billion parameter Llama 3.1-based causal language model developed by deartheiz, fine-tuned using Unsloth and Huggingface's TRL library. This model is optimized for specific tasks related to its fine-tuning data, offering efficient performance due to its training methodology. It leverages the Llama 3.1 architecture for general language understanding and generation, with a context length of 8192 tokens.
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Model Overview
LLM-LuatGiaoThong is an 8 billion parameter language model developed by deartheiz. It is built upon the Llama 3.1 architecture and has been fine-tuned from the unsloth/llama-3.1-8b-bnb-4bit base model. The fine-tuning process utilized the Unsloth library, which enabled a 2x faster training speed, alongside Huggingface's TRL library.
Key Characteristics
- Base Model: Llama 3.1-8B
- Parameters: 8 billion
- Context Length: 8192 tokens
- Training Method: Fine-tuned using Unsloth and Huggingface TRL for accelerated training.
- License: Apache-2.0
Intended Use
This model is designed for applications that can benefit from a Llama 3.1-based model fine-tuned with efficient methods. Its specific fine-tuning data, implied by its name "LuatGiaoThong" (Traffic Law), suggests potential specialization in areas related to traffic regulations or similar domain-specific knowledge. Developers can leverage its Llama 3.1 foundation for general language tasks while benefiting from its specialized fine-tuning for relevant use cases.