A7med-Ame3/Qwen2.5-7B-LiveKit-16bit

TEXT GENERATIONConcurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 25, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold

A7med-Ame3/Qwen2.5-7B-LiveKit-16bit is a 7.6 billion parameter Qwen2.5 model developed by A7med-Ame3. This model was finetuned from unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit, leveraging Unsloth and Huggingface's TRL library for accelerated training. It is optimized for tasks typically handled by instruction-tuned large language models, offering efficient performance due to its 16-bit configuration.

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Model Overview

A7med-Ame3/Qwen2.5-7B-LiveKit-16bit is a 7.6 billion parameter language model developed by A7med-Ame3. It is finetuned from the unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit base model, indicating its foundation in the Qwen2.5 architecture.

Key Characteristics

  • Efficient Training: This model was trained using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process.
  • Base Model: It builds upon an instruction-tuned Qwen2.5 variant, suggesting its suitability for following instructions and engaging in conversational tasks.
  • Parameter Count: With 7.6 billion parameters, it offers a balance between performance and computational requirements.

Use Cases

This model is suitable for applications requiring an instruction-following language model, particularly where efficient deployment and inference are important. Its 16-bit configuration implies a focus on performance and reduced memory footprint compared to full precision models.