balazsgamer918/qwen2.5-14b-balazs-assistant-full

TEXT GENERATIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:14.8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 23, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The balazsgamer918/qwen2.5-14b-balazs-assistant-full is a 14.8 billion parameter Qwen2.5-based causal language model, finetuned by balazsgamer918. It was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. This model is designed for general assistant-style tasks, leveraging its Qwen2.5 architecture and optimized training process.

Loading preview...

Model Overview

The balazsgamer918/qwen2.5-14b-balazs-assistant-full is a 14.8 billion parameter language model, finetuned by balazsgamer918. It is based on the Qwen2.5 architecture, specifically finetuned from unsloth/Qwen2.5-14B-Instruct-bnb-4bit.

Key Characteristics

  • Architecture: Qwen2.5-based, a powerful causal language model family.
  • Parameter Count: 14.8 billion parameters, offering a balance between performance and computational requirements.
  • Training Optimization: This model was finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
  • Context Length: Supports a context length of 32768 tokens, allowing for processing longer inputs and maintaining conversational coherence over extended interactions.

Use Cases

This model is suitable for a variety of assistant-style applications, benefiting from its Qwen2.5 foundation and optimized finetuning. Its capabilities make it a strong candidate for:

  • General conversational AI.
  • Text generation tasks.
  • Instruction following.
  • Applications requiring a robust and efficiently trained large language model.

Finetunes
1 models