yuq-zhou/2026-05-o-b0p3-a0p25-gc0p75-exp-td8p0-tw10p0-mbz-bridge-q3-1p7b

TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:2BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 15, 2026Architecture:Transformer Featherless Exclusive Cold

The 2026-05-o-b0p3-a0p25-gc0p75-exp-td8p0-tw10p0-mbz-bridge-q3-1p7b model by yuq-zhou is a 2 billion parameter language model with a 32,768 token context length. This model is provided as a research artifact backup in standard HuggingFace format. Its primary purpose is to serve as a checkpoint for research and development, offering a base for further experimentation.

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Model Overview

The 2026-05-o-b0p3-a0p25-gc0p75-exp-td8p0-tw10p0-mbz-bridge-q3-1p7b is a 2 billion parameter language model developed by yuq-zhou. It features a substantial context length of 32,768 tokens, allowing it to process and generate longer sequences of text.

Key Characteristics

  • Parameter Count: 2 billion parameters, offering a balance between performance and computational efficiency.
  • Context Length: 32,768 tokens, enabling the model to handle extensive input and generate coherent, long-form content.
  • Format: Provided in the standard HuggingFace format, ensuring compatibility with AutoModelForCausalLM.from_pretrained for easy integration into existing workflows.

Intended Use

This model is primarily released as a research artifact backup. It is suitable for:

  • Research and Development: Serving as a foundational checkpoint for researchers and developers to build upon, fine-tune, or analyze.
  • Experimental Purposes: Ideal for exploring new techniques, architectures, or applications within the domain of large language models.

Limitations

As a research artifact, specific performance benchmarks or detailed training methodologies are not provided in the current documentation. Users should conduct their own evaluations to determine suitability for specific tasks.

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