agurung/Qwen2.5-7B-Instruct-1M-NRL-NCP-GRPO-NLL-PIECEWISE-REWARD

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 21, 2025Architecture:Transformer Featherless Exclusive Cold

agurung/Qwen2.5-7B-Instruct-1M-NRL-NCP-GRPO-NLL-PIECEWISE-REWARD is a 7.6 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. This model is shared by agurung and is designed for general-purpose conversational AI tasks. Its primary use case involves following instructions effectively to generate human-like text responses.

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Overview

This model, agurung/Qwen2.5-7B-Instruct-1M-NRL-NCP-GRPO-NLL-PIECEWISE-REWARD, is an instruction-tuned language model built upon the Qwen2.5 architecture, featuring 7.6 billion parameters. It is designed to understand and execute a wide range of instructions, making it suitable for various natural language processing tasks. The model card indicates that it is a Hugging Face Transformers model, automatically generated, but specific details regarding its development, funding, language, license, and finetuning base are currently marked as "More Information Needed" in the provided README.

Key Capabilities

  • Instruction Following: Designed to accurately interpret and respond to user instructions.
  • General Text Generation: Capable of producing coherent and contextually relevant text.

Good for

  • Conversational AI: Ideal for chatbots, virtual assistants, and interactive applications requiring instruction adherence.
  • Prototyping: Useful for developers needing a capable instruction-tuned model for initial experimentation and development.
  • Research: Can serve as a base for further research into instruction tuning and large language model behavior.

Finetunes
2 models