shabieh2/ms_0431_merged
The shabieh2/ms_0431_merged model is a 70 billion parameter Llama-3.3 instruction-tuned language model, developed by shabieh2. This model was finetuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general language generation tasks, leveraging its large parameter count and instruction-tuning for broad applicability.
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Model Overview
The shabieh2/ms_0431_merged is a 70 billion parameter instruction-tuned language model based on the Llama-3.3 architecture. Developed by shabieh2, this model was finetuned from unsloth/llama-3.3-70b-instruct-unsloth-bnb-4bit.
Key Characteristics
- Architecture: Llama-3.3 based, instruction-tuned.
- Parameter Count: 70 billion parameters, providing substantial capacity for complex tasks.
- Training Efficiency: Finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Context Length: Supports an 8192-token context window.
Use Cases
This model is suitable for a wide range of natural language processing applications due to its instruction-tuned nature and large parameter count. It can be effectively used for:
- General text generation and completion.
- Instruction following and conversational AI.
- Summarization and question answering tasks.