nsomazr/blood-donation-gemma3-1bb-merged-16bit

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:1BQuant:BF16Ctx Length:32kPublished:Apr 5, 2026License:apache-2.0Architecture:Transformer Open Weights Warm

The nsomazr/blood-donation-gemma3-1bb-merged-16bit is a 1 billion parameter Gemma 3-1B-IT-based causal language model developed by nsomazr, fine-tuned from unsloth/gemma-3-1b-it-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling faster training. With a context length of 32768 tokens, it is optimized for specific tasks related to blood donation, leveraging its efficient fine-tuning process.

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Model Overview

The nsomazr/blood-donation-gemma3-1bb-merged-16bit is a 1 billion parameter language model developed by nsomazr. It is fine-tuned from the unsloth/gemma-3-1b-it-bnb-4bit base model, leveraging the Gemma 3-1B-IT architecture. This model was specifically trained using the Unsloth framework in conjunction with Huggingface's TRL library, which facilitated a 2x faster training process.

Key Characteristics

  • Base Model: Gemma 3-1B-IT
  • Parameter Count: 1 billion parameters
  • Training Efficiency: Utilizes Unsloth for accelerated fine-tuning.
  • Context Length: Supports a substantial context window of 32768 tokens.

Potential Use Cases

This model is likely specialized for tasks related to its fine-tuning domain, which, based on its name, suggests applications in the blood donation sector. Developers might consider this model for:

  • Generating text or answering questions within the blood donation context.
  • Assisting with information retrieval or summarization related to blood donation processes, eligibility, or campaigns.
  • Developing applications requiring a compact yet capable language model with a focus on specific domain knowledge.