Rajesh507/ecomm-db-stage1-merged

TEXT GENERATIONConcurrent Unit Cost:1Model Size:1.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 12, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Rajesh507/ecomm-db-stage1-merged is a 1.5 billion parameter Qwen2-based language model, developed by Rajesh507. This model was finetuned using Unsloth and Huggingface's TRL library, enabling faster training. It is optimized for specific tasks related to e-commerce databases, leveraging its efficient finetuning process.

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Model Overview

Rajesh507/ecomm-db-stage1-merged is a 1.5 billion parameter language model based on the Qwen2 architecture. It was developed by Rajesh507 and finetuned from unsloth/qwen2.5-coder-1.5b-bnb-4bit.

Key Characteristics

  • Architecture: Qwen2-based, a causal language model.
  • Parameter Count: 1.5 billion parameters, making it a relatively compact model.
  • Training Efficiency: Finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
  • Context Length: Supports a context length of 32768 tokens.

Intended Use Cases

This model is specifically designed for applications related to e-commerce databases, likely involving tasks such as data extraction, query generation, or content understanding within an e-commerce context. Its efficient finetuning process suggests it is optimized for performance in its specialized domain.