ganesh714/arq_m1_chairs_DS_r1_Q7

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 23, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The ganesh714/arq_m1_chairs_DS_r1_Q7 is a 7.6 billion parameter Qwen2 model developed by ganesh714. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is based on the unsloth/deepseek-r1-distill-qwen-7b-unsloth-bnb-4bit architecture and is optimized for efficient deployment and performance.

Loading preview...

Model Overview

The ganesh714/arq_m1_chairs_DS_r1_Q7 is a 7.6 billion parameter Qwen2 language model, fine-tuned by ganesh714. This model leverages the unsloth/deepseek-r1-distill-qwen-7b-unsloth-bnb-4bit as its base architecture.

Key Characteristics

  • Efficient Training: The model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
  • Parameter Count: With 7.6 billion parameters, it offers a balance between performance and computational efficiency.
  • Context Length: The model supports a context length of 32768 tokens, allowing it to process and generate longer sequences of text.

Use Cases

This model is suitable for applications requiring a Qwen2-based language model that benefits from optimized training and efficient inference. Its 7.6B parameter size makes it a good candidate for tasks where larger models might be too resource-intensive, while still providing robust language understanding and generation capabilities.