yuq-zhou/2026-05-o-b0p3-a1p0-gc0p5-exp-td4p0-tw5p0-r1-7-fixed-20260804-last

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-td4p0-tw5p0-r1-7-fixed-20260804-last 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. It is suitable for researchers and developers working with experimental language models and requires direct integration via AutoModelForCausalLM.from_pretrained. Its primary utility lies in serving as a checkpoint for further research and development.

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Overview

This model, named 2026-05-o-b0p3-a1p0-gc0p5-exp-td4p0-tw5p0-r1-7-fixed-20260804-last, is a 7.6 billion parameter causal language model developed by yuq-zhou. It is provided as a research artifact backup, formatted for direct use with HuggingFace's AutoModelForCausalLM.from_pretrained.

Key Characteristics

  • Parameter Count: 7.6 billion parameters.
  • Context Length: Supports a substantial context window of 32768 tokens.
  • Format: Standard HuggingFace checkpoint, ensuring compatibility with existing tools and workflows.

Intended Use

This model is primarily intended as a research artifact. It serves as a checkpoint for ongoing or future research and development efforts. Users should consider it a foundational component for experimental work rather than a production-ready solution.

Limitations

As a research artifact, specific performance metrics, training details, or fine-tuning instructions are not provided in the accompanying documentation. Users should expect to conduct their own evaluations and potentially further fine-tuning for specific applications.