AmberYifan/capsd-less-ultra-opc-marin-8b-base-code_less_b4000_s0

TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Aug 30, 2026License:otherArchitecture:Transformer Featherless Exclusive Cold

AmberYifan/capsd-less-ultra-opc-marin-8b-base-code_less_b4000_s0 is an 8 billion parameter language model, fine-tuned from marin-community/marin-8b-base. This model was trained on the capsd_marin-8b-base-n80000-opc__mix_code_less_b4000_s0 dataset with a context length of 8192 tokens. It is a specialized iteration of the Marin 8B base model, focusing on specific dataset characteristics.

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Model Overview

AmberYifan/capsd-less-ultra-opc-marin-8b-base-code_less_b4000_s0 is an 8 billion parameter language model, fine-tuned from the marin-community/marin-8b-base architecture. This model was specifically trained on the capsd_marin-8b-base-n80000-opc__mix_code_less_b4000_s0 dataset, indicating a specialized training focus.

Training Details

The model underwent a fine-tuning process with the following key hyperparameters:

  • Learning Rate: 1e-05
  • Batch Size: 2 (train), 8 (eval)
  • Gradient Accumulation Steps: 8
  • Optimizer: AdamW with betas=(0.9, 0.999) and epsilon=1e-08
  • LR Scheduler: Cosine type with 0.03 warmup steps
  • Epochs: 1

The training utilized a multi-GPU setup with 4 devices, resulting in a total train batch size of 64 and a total evaluation batch size of 32. The model was developed using 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 are not detailed in the provided information, its fine-tuning on a specialized dataset suggests potential applications related to the characteristics of capsd_marin-8b-base-n80000-opc__mix_code_less_b4000_s0.