yuq-zhou/2026-05-o-b1p0-a1p0-gc0p5-exp-td4p0-tw10p0-mbz-r1-7

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 10, 2026Architecture:Transformer Featherless Exclusive Cold

The yuq-zhou/2026-05-o-b1p0-a1p0-gc0p5-exp-td4p0-tw10p0-mbz-r1-7 model is a 7.6 billion parameter causal language model with a 32,768 token context length. Developed by yuq-zhou, this model is provided as a standard HuggingFace checkpoint. It serves as a research artifact backup, indicating its primary purpose for internal research and development.

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Model Overview

The yuq-zhou/2026-05-o-b1p0-a1p0-gc0p5-exp-td4p0-tw10p0-mbz-r1-7 is a 7.6 billion parameter causal language model, offering a substantial context window of 32,768 tokens. This model is made available in the standard HuggingFace format, allowing for straightforward integration using AutoModelForCausalLM.from_pretrained.

Key Characteristics

  • Parameter Count: 7.6 billion parameters, placing it in the medium-sized LLM category.
  • Context Length: Features a 32,768 token context window, enabling processing of longer inputs and maintaining coherence over extended conversations or documents.
  • Format: Provided as a standard HuggingFace checkpoint, ensuring compatibility with existing HuggingFace ecosystem tools and libraries.

Intended Use

This model is explicitly designated as a "research artifact backup." This suggests its primary utility is for internal research, experimentation, and as a developmental checkpoint rather than for broad production deployment. Users should consider its nature as a research artifact when evaluating its suitability for specific applications.