Navneetkumar11/cloud-agent
TEXT GENERATIONConcurrency Cost:1Model Size:1BQuant:BF16Ctx Length:32kPublished:Apr 23, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
Navneetkumar11/cloud-agent is a 1 billion parameter Llama-3.2-based instruction-tuned causal language model developed by Navneetkumar11. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
Navneetkumar11/cloud-agent is a 1 billion parameter instruction-tuned language model, developed by Navneetkumar11. It is based on the Llama-3.2 architecture and was fine-tuned from unsloth/llama-3.2-1b-instruct-unsloth-bnb-4bit.
Key Characteristics
- Efficient Training: This model was fine-tuned using Unsloth and Huggingface's TRL library, which allowed for a 2x faster training process compared to standard methods.
- Llama-3.2 Base: Built upon the Llama-3.2 architecture, providing a solid foundation for instruction-following capabilities.
- Parameter Count: With 1 billion parameters, it offers a balance between performance and computational efficiency.
Good For
- Instruction Following: Suitable for tasks requiring the model to adhere to specific instructions.
- Resource-Efficient Deployment: Its smaller size and efficient training suggest potential for deployment in environments with limited computational resources.
- Experimentation: Ideal for developers looking to leverage models fine-tuned with Unsloth for faster iteration and development.