AmberYifan/capsd-marin-8b-base-code_ifd_b10000_s0

TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Aug 5, 2026License:otherArchitecture:Transformer Featherless Exclusive Cold

The AmberYifan/capsd-marin-8b-base-code_ifd_b10000_s0 is an 8 billion parameter language model, fine-tuned from marin-community/marin-8b-base. This model is specifically trained on a code-focused dataset, capsd_marin-8b-base-n80000-opc__mix_code_ifd_b10000_s0, indicating an optimization for code generation and understanding tasks. It features an 8192-token context length, making it suitable for processing substantial code blocks.

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Model Overview

The AmberYifan/capsd-marin-8b-base-code_ifd_b10000_s0 is an 8 billion parameter language model, fine-tuned from the marin-community/marin-8b-base architecture. This iteration has been specialized through training on the capsd_marin-8b-base-n80000-opc__mix_code_ifd_b10000_s0 dataset, suggesting a focus on code-related applications.

Training Details

The model underwent a single epoch of training with a learning rate of 1e-05. Key training hyperparameters included:

  • Optimizer: ADAMW_TORCH with betas=(0.9, 0.999) and epsilon=1e-08
  • Batch Size: 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.
  • Scheduler: Cosine learning rate scheduler with 0.03 warmup steps.
  • Environment: Distributed training across 4 GPUs.

Framework Versions

The training utilized:

  • Transformers 5.7.0
  • Pytorch 2.13.0+cu130
  • Datasets 4.0.0
  • Tokenizers 0.22.2

Potential Use Cases

Given its fine-tuning on a code-specific dataset, this model is likely optimized for tasks such as code generation, code completion, debugging assistance, or understanding code logic.

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