yuq-zhou/2026-05-leash-t2k-q3-1p7

TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:2BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 18, 2026Architecture:Transformer Featherless Exclusive Cold

The yuq-zhou/2026-05-leash-t2k-q3-1p7 is a 2 billion parameter causal language model provided in a standard HuggingFace format. This model serves as a research artifact backup, making it suitable for developers and researchers needing to access a specific checkpoint for experimental or archival purposes. Its primary utility lies in its availability as a foundational model for further fine-tuning or analysis within research contexts.

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Model Overview

The yuq-zhou/2026-05-leash-t2k-q3-1p7 is a 2 billion parameter causal language model. It is provided as a standard HuggingFace checkpoint, making it directly compatible with AutoModelForCausalLM.from_pretrained for easy integration into existing workflows.

Key Characteristics

  • Parameter Count: 2 billion parameters, offering a balance between computational efficiency and model capacity.
  • Context Length: Supports a substantial context window of 32768 tokens, allowing for processing and generating longer sequences of text.
  • Format: Distributed in the widely adopted HuggingFace format, ensuring broad compatibility and ease of use within the ML ecosystem.

Primary Use Case

This model is specifically designated as a research artifact backup. Its main purpose is to serve as a stable and accessible checkpoint for research and development. It is ideal for:

  • Archival: Storing a specific state of a model for future reference or reproducibility.
  • Experimental Baselines: Providing a consistent starting point for comparative studies or new fine-tuning experiments.
  • Developer Access: Allowing developers to load and inspect a particular model version for analysis or integration into custom applications.