AmberYifan/capsd-less-humaneval-opc-marin-8b-base-code_less_b8000_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-humaneval-opc-marin-8b-base-code_less_b8000_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_b8000_s0 dataset, with a context length of 8192 tokens. It is a specialized iteration focusing on specific code-related tasks, derived from its base model.

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Model Overview

This model, AmberYifan/capsd-less-humaneval-opc-marin-8b-base-code_less_b8000_s0, is an 8 billion parameter language model. It is a fine-tuned version of the marin-community/marin-8b-base model, specifically adapted using the capsd_marin-8b-base-n80000-opc__mix_code_less_b8000_s0 dataset.

Training Details

The model was trained with a learning rate of 1e-05, a train_batch_size of 2, and an eval_batch_size of 8. It utilized a multi-GPU distributed setup with 4 devices and a gradient_accumulation_steps of 8, resulting in a total_train_batch_size of 64. The optimizer used was ADAMW_TORCH with default betas and epsilon, and the learning rate scheduler was set to cosine with 0.03 warmup steps over 1 epoch. The training was conducted using Transformers 5.7.0, Pytorch 2.13.0+cu130, Datasets 4.0.0, and Tokenizers 0.22.2.

Key Characteristics

  • Base Model: Fine-tuned from marin-community/marin-8b-base.
  • Parameter Count: 8 billion parameters.
  • Context Length: Supports a context window of 8192 tokens.
  • Training Dataset: Specialized training on capsd_marin-8b-base-n80000-opc__mix_code_less_b8000_s0.