AmberYifan/capsd-less-fast-opc-marin-8b-base-code_less_b4000_s0
The AmberYifan/capsd-less-fast-opc-marin-8b-base-code_less_b4000_s0 model is an 8 billion parameter language model, fine-tuned from marin-community/marin-8b-base. It is specifically adapted using the capsd_marin-8b-base-n80000-opc__mix_code_less_b4000_s0 dataset, suggesting an optimization for code-related tasks. With a context length of 8192 tokens, this model is designed for applications requiring robust code understanding and generation capabilities.
Loading preview...
Model Overview
This model, AmberYifan/capsd-less-fast-opc-marin-8b-base-code_less_b4000_s0, is an 8 billion parameter language model. It is a fine-tuned variant of the marin-community/marin-8b-base architecture, specifically adapted for enhanced performance in certain domains.
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 Data: Adapted using the
capsd_marin-8b-base-n80000-opc__mix_code_less_b4000_s0dataset, indicating a focus on code-related tasks.
Training Details
The model was trained with a learning rate of 1e-05, a train_batch_size of 2, and a gradient_accumulation_steps of 8, resulting in a total_train_batch_size of 64. It utilized a cosine learning rate scheduler with 0.03 warmup steps over 1 epoch. The training was conducted on 4 GPUs using a multi-GPU distributed setup.
Potential Use Cases
Given its fine-tuning on a code-centric dataset, this model is likely suitable for:
- Code generation and completion.
- Code understanding and analysis.
- Assisting with programming tasks.