AmberYifan/capsd-marin-8b-base-math_ifd_b1000_s0

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

AmberYifan/capsd-marin-8b-base-math_ifd_b1000_s0 is an 8 billion parameter language model fine-tuned from marin-community/marin-8b-base. This model is specifically adapted for mathematical tasks, leveraging the capsd_marin-8b-base-n80000-numina__mix_math_ifd_b1000_s0 dataset. It is designed to enhance performance in mathematical reasoning and problem-solving contexts. The model was trained with a context length of 8192 tokens.

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Model Overview

AmberYifan/capsd-marin-8b-base-math_ifd_b1000_s0 is an 8 billion parameter language model, fine-tuned from the marin-community/marin-8b-base architecture. This iteration focuses on improving mathematical capabilities through specialized training.

Key Characteristics

  • Base Model: Fine-tuned from marin-community/marin-8b-base.
  • Parameter Count: 8 billion parameters.
  • Context Length: Supports an 8192-token context window.
  • Specialized Training: Enhanced using the capsd_marin-8b-base-n80000-numina__mix_math_ifd_b1000_s0 dataset, indicating a focus on mathematical instruction following and problem-solving.

Training Details

The model underwent training with specific hyperparameters:

  • Learning Rate: 1e-05
  • Optimizer: ADAMW_TORCH
  • Epochs: 1
  • Batch Size: A total training batch size of 64 (with gradient accumulation).

Intended Use Cases

This model is primarily intended for applications requiring strong mathematical reasoning and accurate numerical processing. Its fine-tuning on a math-specific dataset suggests suitability for tasks such as:

  • Solving mathematical problems.
  • Generating mathematical explanations.
  • Assisting with quantitative analysis.

Finetunes
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