Senthi1Kumar/SciLlama-3.2-3B
TEXT GENERATIONPricing:Input $0.2036 / Output $1.34Concurrent Unit Cost:1Model Size:3.2BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Mar 9, 2025License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold
Senthi1Kumar/SciLlama-3.2-3B is a 3.2 billion parameter Llama-based instruction-tuned causal language model developed by SenthilKumarN. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language understanding and generation tasks, leveraging its efficient training methodology.
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Model Overview
Senthi1Kumar/SciLlama-3.2-3B is a 3.2 billion parameter Llama-based instruction-tuned model developed by SenthilKumarN. It was fine-tuned from unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit with a focus on efficient training.
Key Capabilities
- Efficient Training: This model was trained 2x faster using Unsloth and Huggingface's TRL library, highlighting advancements in training methodology for Llama-based architectures.
- Instruction Following: As an instruction-tuned model, it is designed to understand and respond to user prompts effectively, making it suitable for various conversational and task-oriented applications.
- Llama Architecture: Built upon the Llama 3.2 architecture, it inherits the foundational capabilities of this model family, providing a robust base for language tasks.
Good For
- General Language Tasks: Suitable for a wide range of applications requiring text generation, summarization, question answering, and conversational AI.
- Resource-Efficient Deployment: Its 3.2 billion parameter size makes it a good candidate for scenarios where computational resources are a consideration, offering a balance between performance and efficiency.
- Experimentation with Unsloth: Developers interested in leveraging Unsloth's fast training capabilities for Llama models can use this as a reference or starting point.