yuq-zhou/2026-05-o-b0p3-a1p0-gc0p5-exp-td2p0-tw5p0-shufdag-q2-m-7

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:7.6BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 5, 2026Architecture:Transformer Featherless Exclusive Cold

The yuq-zhou/2026-05-o-b0p3-a1p0-gc0p5-exp-td2p0-tw5p0-shufdag-q2-m-7 is a 7.6 billion parameter causal language model developed by yuq-zhou. This model is provided as a research artifact backup in standard HuggingFace format, supporting a context length of 32768 tokens. Its primary purpose is as a checkpoint for research, offering a base for further experimentation and development.

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Model Overview

The yuq-zhou/2026-05-o-b0p3-a1p0-gc0p5-exp-td2p0-tw5p0-shufdag-q2-m-7 is a 7.6 billion parameter causal language model. Developed by yuq-zhou, this model is distributed in the standard HuggingFace format, making it readily compatible with AutoModelForCausalLM.from_pretrained for easy integration into existing workflows.

Key Characteristics

  • Parameter Count: 7.6 billion parameters.
  • Context Length: Supports a substantial context window of 32768 tokens.
  • Format: Provided as a model checkpoint in standard HuggingFace format.

Intended Use

This model is primarily intended as a research artifact backup. It serves as a foundational checkpoint for researchers and developers looking to build upon or analyze its architecture and training. Its large context window makes it suitable for tasks requiring extensive input understanding or generation.

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