AmberYifan/capsd-less-ultra-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-ultra-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 a specific dataset, capsd_marin-8b-base-n80000-opc__mix_code_less_b8000_s0, with a context length of 8192 tokens. Its fine-tuning process suggests a specialization, though specific capabilities and intended uses require further information.

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Model Overview

AmberYifan/capsd-less-ultra-opc-marin-8b-base-code_less_b8000_s0 is an 8 billion parameter language model, fine-tuned from the marin-community/marin-8b-base architecture. It was trained using a specific dataset, capsd_marin-8b-base-n80000-opc__mix_code_less_b8000_s0, indicating a specialized application or domain.

Training Details

The model underwent a single epoch of training 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 a cosine learning rate scheduler. The training utilized a multi-GPU setup with 4 devices.

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.
  • Training Frameworks: Developed using Transformers 5.7.0, Pytorch 2.13.0+cu130, Datasets 4.0.0, and Tokenizers 0.22.2.

Further details regarding its specific capabilities, intended uses, and limitations are not explicitly provided in the current model card.