ganesh714/arq_m1_chairs_think_Q7b_C

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 24, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The ganesh714/arq_m1_chairs_think_Q7b_C is a 7.6 billion parameter Qwen2-based causal language model, fine-tuned by ganesh714. This model was efficiently trained using Unsloth and Huggingface's TRL library, building upon the unsloth/qwen2.5-coder-7b-instruct-bnb-4bit base. It is designed for general language understanding and generation tasks, leveraging its 32K context length for processing longer inputs.

Loading preview...

Model Overview

The ganesh714/arq_m1_chairs_think_Q7b_C is a 7.6 billion parameter language model developed by ganesh714. It is fine-tuned from the unsloth/qwen2.5-coder-7b-instruct-bnb-4bit base model, indicating a foundation optimized for coding-related tasks. The fine-tuning process leveraged Unsloth and Huggingface's TRL library, which enabled a 2x faster training speed.

Key Characteristics

  • Base Model: Qwen2.5-Coder-7B-Instruct
  • Parameter Count: 7.6 billion parameters
  • Context Length: 32,768 tokens
  • Training Efficiency: Utilized Unsloth for accelerated fine-tuning.

Potential Use Cases

Given its base as a 'coder' instruction model, this fine-tuned version is likely suitable for:

  • Code generation and completion.
  • Instruction following in technical domains.
  • General text generation and understanding where a robust Qwen2.5 foundation is beneficial.