yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_KLEff_smooth_submax_reg0.25_checkpoint-25

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_smooth_submax_reg0.25_checkpoint-25 is a 4 billion parameter language model with a 32768 token context length. Developed by yunjae-won, this model is a checkpoint from a training run, indicating it is likely a base or intermediate model intended for further fine-tuning or research. Its specific architecture and primary differentiators are not detailed, suggesting it serves as a foundational component for specialized applications.

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Model Overview

This model, yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_KLEff_smooth_submax_reg0.25_checkpoint-25, is a 4 billion parameter language model developed by yunjae-won. It features a substantial context length of 32768 tokens, indicating its potential for processing and generating long sequences of text. As a checkpoint from a training process, it represents an intermediate state of a larger model development effort.

Key Characteristics

  • Parameter Count: 4 billion parameters.
  • Context Length: Supports a context window of 32768 tokens.
  • Development Stage: This is a training checkpoint, suggesting it may be a base model or part of an ongoing research project.
  • Developer: Created by yunjae-won.

Potential Use Cases

Given its status as a training checkpoint and the lack of specific use case details, this model is likely intended for:

  • Further Fine-tuning: Serving as a robust base for specialized downstream tasks.
  • Research and Experimentation: Exploring different fine-tuning strategies or architectural modifications.
  • Foundation for Custom Applications: Building domain-specific language models where a large context window is beneficial.