AmberYifan/capsd-less-fast-opc-marin-8b-base-code_less_b8000_s0
The AmberYifan/capsd-less-fast-opc-marin-8b-base-code_less_b8000_s0 model is an 8 billion parameter language model, fine-tuned from marin-community/marin-8b-base. It was trained on the capsd_marin-8b-base-n80000-opc__mix_code_less_b8000_s0 dataset, suggesting an optimization for code-related tasks. This model is designed for applications requiring a compact yet capable language model with a focus on code understanding or generation, operating within an 8192 token context length.
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Model Overview
This model, AmberYifan/capsd-less-fast-opc-marin-8b-base-code_less_b8000_s0, is an 8 billion parameter language model. It is a fine-tuned variant of the marin-community/marin-8b-base architecture, specifically adapted through further training.
Key Characteristics
- Base Model: Fine-tuned from
marin-community/marin-8b-base. - Parameter Count: 8 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports an 8192 token context window.
- Training Data: Fine-tuned on the
capsd_marin-8b-base-n80000-opc__mix_code_less_b8000_s0dataset, indicating a potential specialization in code-related tasks or data.
Training Details
The model underwent a single epoch of training with a learning rate of 1e-05, using an AdamW optimizer. Training was distributed across 4 GPUs with a total batch size of 64, utilizing gradient accumulation steps of 8. The training process leveraged Transformers 5.7.0, Pytorch 2.13.0+cu130, Datasets 4.0.0, and Tokenizers 0.22.2.
Potential Use Cases
Given its fine-tuning on a dataset with "code" in its name, this model is likely suitable for:
- Code generation and completion.
- Code analysis and understanding tasks.
- Applications requiring a language model with enhanced capabilities in programming contexts.