Samridhi24/Agent-Hire-1B-Merged
Samridhi24/Agent-Hire-1B-Merged is a 1 billion parameter Llama-3.2-based causal language model developed by Samridhi24. Finetuned using Unsloth and Huggingface's TRL library, this model was trained for enhanced performance. With a 32768 token context length, it is optimized for specific agent-hire related tasks.
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Model Overview
Samridhi24/Agent-Hire-1B-Merged is a 1 billion parameter language model, finetuned from unsloth/Llama-3.2-1B-bnb-4bit. Developed by Samridhi24, this model leverages the Llama-3.2 architecture and was trained with a focus on efficiency using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process.
Key Characteristics
- Base Model: Llama-3.2-1B-bnb-4bit
- Parameter Count: 1 billion parameters
- Context Length: 32768 tokens
- Training Efficiency: Utilizes Unsloth for accelerated finetuning.
Potential Use Cases
This model is suitable for applications requiring a compact yet capable language model, particularly where the finetuning process has optimized it for specific agent-hire related functionalities. Its efficient training methodology makes it a good candidate for rapid iteration and deployment in resource-constrained environments.