AmberYifan/capsd-marin-8b-base-code_cap_b4000_s0
AmberYifan/capsd-marin-8b-base-code_cap_b4000_s0 is an 8 billion parameter language model, fine-tuned from marin-community/marin-8b-base. This model is specifically adapted for code-related tasks, leveraging a specialized dataset for its training. It is designed to enhance performance in code generation and understanding within an 8192 token context window.
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Model Overview
AmberYifan/capsd-marin-8b-base-code_cap_b4000_s0 is an 8 billion parameter language model, fine-tuned from the marin-community/marin-8b-base architecture. This model has been specifically adapted through further training on the capsd_marin-8b-base-n10000__mix_code_cap_b4000_s0 dataset.
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 Focus: The fine-tuning process utilized a dataset specifically geared towards code, suggesting an optimization for code-related tasks.
Training Details
The model was trained with a learning rate of 1e-05, a total batch size of 64 (across 4 GPUs with 16 gradient accumulation steps), and a cosine learning rate scheduler with 0 warmup steps. The training consisted of 1 epoch. The training environment included Transformers 5.7.0, Pytorch 2.13.0+cu130, Datasets 4.0.0, and Tokenizers 0.22.2.
Intended Use Cases
While specific intended uses are not detailed, the fine-tuning on a code-centric dataset implies its suitability for applications requiring code generation, completion, or analysis. Developers looking for a specialized 8B model for programming tasks may find this model relevant.