yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_KLEff_reg2_checkpoint-125
The yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_KLEff_reg2_checkpoint-125 is a 4 billion parameter language model developed by yunjae-won. This model is a checkpoint from a training run, indicating it is likely part of an ongoing development or research project. With a context length of 32768 tokens, it is designed to process and generate long sequences of text. Its specific differentiators and primary use cases are not detailed in the provided information, suggesting it may be a base model or an intermediate result.
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Model Overview
The yunjae-won/OPSD_4b_noclip_default_lr1e-5_bs128_KLEff_reg2_checkpoint-125 is a 4 billion parameter language model developed by yunjae-won. This model is identified as a checkpoint, suggesting it is an intermediate state from a training process rather than a fully released, instruction-tuned model. It supports a substantial context length of 32768 tokens, enabling it to handle extensive textual inputs and outputs.
Key Characteristics
- Developer: yunjae-won
- Parameter Count: 4 billion parameters
- Context Length: 32768 tokens
- Model Type: Checkpoint from a training run
Current Status and Usage
As a checkpoint, detailed information regarding its specific architecture, training data, intended applications, or performance benchmarks is not provided in the model card. Users interested in its capabilities would need to investigate the broader project it belongs to. The model card indicates that further information is needed across various sections, including direct use, downstream use, bias, risks, limitations, training details, and evaluation results. This suggests it is primarily for internal development or research purposes by its creator until more details are made available.