SKNahin/Qwen2.5-7B-Instruct-Modified

TEXT GENERATIONConcurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 9, 2026Architecture:Transformer Featherless Exclusive Cold

SKNahin/Qwen2.5-7B-Instruct-Modified is a 7.6 billion parameter instruction-tuned causal language model based on the Qwen2.5 architecture. This model is a modified version of the original Qwen2.5-7B-Instruct, featuring a 32768-token context length. It is designed for general-purpose instruction following, leveraging its substantial parameter count and extended context window for diverse NLP tasks.

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Overview

This model, SKNahin/Qwen2.5-7B-Instruct-Modified, is an instruction-tuned variant of the Qwen2.5-7B architecture, featuring 7.6 billion parameters. It is designed to follow instructions effectively across a broad range of natural language processing tasks. A key characteristic of this modified version is its extended context length of 32768 tokens, which allows it to process and generate longer sequences of text, enhancing its utility for complex conversational or document-based applications.

Key Capabilities

  • Instruction Following: Designed to accurately interpret and execute user instructions.
  • Extended Context Window: Supports a 32768-token context length, beneficial for handling lengthy inputs and maintaining coherence over extended interactions.
  • General-Purpose NLP: Suitable for a wide array of tasks due to its instruction-tuned nature and substantial parameter count.

Good for

  • Applications requiring robust instruction following.
  • Tasks that benefit from processing long documents or maintaining long conversational histories.
  • General text generation, summarization, and question-answering where a large context is advantageous.

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