AmberYifan/capsdnum-marin-8b-base-code_ppl_b2000_s0

TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Jul 17, 2026License:otherArchitecture:Transformer Featherless Exclusive Cold

The AmberYifan/capsdnum-marin-8b-base-code_ppl_b2000_s0 model is a fine-tuned version of the marin-community/marin-8b-base architecture. This model has been specialized through fine-tuning on the capsd_marin-8b-base-n80000-opc__mix_code_ppl_b2000_s0 dataset. It is intended for applications requiring a language model with enhanced capabilities derived from this specific fine-tuning process. Further details on its exact parameter count and context length are not specified in the provided information.

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Model Overview

AmberYifan/capsdnum-marin-8b-base-code_ppl_b2000_s0 is a fine-tuned language model based on the marin-community/marin-8b-base architecture. This model has undergone specialized training on the capsd_marin-8b-base-n80000-opc__mix_code_ppl_b2000_s0 dataset, indicating a focus on specific data characteristics or tasks related to this dataset.

Training Details

The model was trained using the following key hyperparameters:

  • Learning Rate: 1e-05
  • Batch Sizes: train_batch_size of 2, eval_batch_size of 8
  • Gradient Accumulation: 8 steps, leading to a total_train_batch_size of 64
  • Optimizer: ADAMW_TORCH with standard betas and epsilon
  • LR Scheduler: Cosine type with 0.03 warmup steps
  • Epochs: 1

The training utilized a multi-GPU setup with 4 devices. The development environment included Transformers 5.7.0, Pytorch 2.13.0+cu130, Datasets 4.0.0, and Tokenizers 0.22.2.

Intended Use

While specific intended uses and limitations require more information, the fine-tuning on a specialized dataset suggests its application in areas aligned with the characteristics of capsd_marin-8b-base-n80000-opc__mix_code_ppl_b2000_s0.

Finetunes
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