yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_KLEff_reg0.05_checkpoint-75

TEXT GENERATIONConcurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 14, 2026Architecture:Transformer Featherless Exclusive Cold

The yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_KLEff_reg0.05_checkpoint-75 is a 4 billion parameter language model with a 32,768 token context length. This model's specific architecture, training details, and primary differentiators are not explicitly provided in its current model card. Further information is needed to determine its unique capabilities or optimized use cases compared to other LLMs.

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Model Overview

This model, yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_KLEff_reg0.05_checkpoint-75, is a language model with 4 billion parameters and a substantial context length of 32,768 tokens. The model card indicates it is a Hugging Face Transformers model, but specific details regarding its architecture, development, training data, and intended applications are currently marked as "More Information Needed."

Key Characteristics

  • Parameter Count: 4 billion parameters.
  • Context Length: Supports a long context window of 32,768 tokens.

Current Limitations

As per the provided model card, comprehensive information regarding the following aspects is not yet available:

  • Model Type and Architecture: Specifics on the underlying model architecture are not detailed.
  • Development and Funding: The developers, funders, and contributors are not specified.
  • Training Data and Procedure: Details on the datasets used for training, preprocessing steps, and hyperparameters are missing.
  • Evaluation Results: No performance benchmarks or evaluation metrics are provided.
  • Intended Uses: Direct and downstream use cases are not defined, making it difficult to assess its suitability for specific tasks.
  • Bias, Risks, and Limitations: While acknowledged, specific biases, risks, and limitations are not outlined.

Recommendations

Users should be aware that critical information for understanding this model's capabilities, performance, and appropriate use cases is currently absent. It is recommended to await further updates to the model card for detailed insights into its technical specifications, training, and evaluation before deployment.

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