AmberYifan/capsd-marin-8b-base-code_qurating_b2000_s0

TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Jul 29, 2026License:otherArchitecture:Transformer Featherless Exclusive Cold

AmberYifan/capsd-marin-8b-base-code_qurating_b2000_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_qurating_b2000_s0 dataset, indicating a specialization in code-related tasks. It utilizes an 8192-token context length and was trained with a learning rate of 1e-05 over one epoch.

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Model Overview

AmberYifan/capsd-marin-8b-base-code_qurating_b2000_s0 is an 8 billion parameter language model, fine-tuned from the marin-community/marin-8b-base architecture. This model has been specifically adapted using the capsd_marin-8b-base-n80000-opc__mix_code_qurating_b2000_s0 dataset, suggesting a focus on code generation, analysis, or related programming tasks.

Training Details

The model underwent a single training epoch with a learning rate of 1e-05. Key hyperparameters included a train_batch_size of 2, eval_batch_size of 8, and a gradient_accumulation_steps of 8, resulting in a total_train_batch_size of 64. The optimizer used was ADAMW_TORCH with cosine learning rate scheduling and a warmup of 0.03 steps. The training was conducted across 4 GPUs.

Potential Use Cases

Given its fine-tuning on a code-centric dataset, this model is likely suitable for applications requiring:

  • Code completion and generation.
  • Code summarization or explanation.
  • Debugging assistance.
  • Refactoring suggestions.