AmberYifan/capsd-marin-8b-base-code_kcenter_b16000_s0

TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Aug 6, 2026License:otherArchitecture:Transformer Featherless Exclusive Cold

AmberYifan/capsd-marin-8b-base-code_kcenter_b16000_s0 is an 8 billion parameter language model fine-tuned from marin-community/marin-8b-base. This model was specifically trained on the capsd_marin-8b-base-n80000-opc__mix_code_kcenter_b16000_s0 dataset, indicating a specialization in code-related tasks. It operates with an 8192-token context length, making it suitable for processing moderately long code sequences.

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Model Overview

AmberYifan/capsd-marin-8b-base-code_kcenter_b16000_s0 is an 8 billion parameter language model, fine-tuned from the marin-community/marin-8b-base architecture. This model has been specialized through training on the capsd_marin-8b-base-n80000-opc__mix_code_kcenter_b16000_s0 dataset, suggesting an optimization for code-centric applications.

Key Training Details

The model underwent a fine-tuning process with specific hyperparameters:

  • Learning Rate: 1e-05
  • Batch Size: A train_batch_size of 2 and eval_batch_size of 8, accumulating gradients over 8 steps for an effective total_train_batch_size of 64.
  • Optimizer: ADAMW_TORCH with standard betas and epsilon.
  • Scheduler: Cosine learning rate scheduler with 0.03 warmup steps.
  • Epochs: Trained for 1 epoch.

Intended Use

While specific intended uses and limitations require further information, the fine-tuning on a code-focused dataset implies its primary utility lies in code generation, completion, or analysis tasks. Developers should consider its 8192-token context length for handling relevant code snippets.

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