shopifyinterngrinder/sidekick-autocomplete-06b-sft-real
The shopifyinterngrinder/sidekick-autocomplete-06b-sft-real model is a 0.8 billion parameter language model fine-tuned from Qwen/Qwen3-0.6B. It was specifically trained using the shopifyinterngrinder/sidekick-autocomplete-data-real dataset for 3 epochs with a maximum sequence length of 512. This model is optimized for autocomplete tasks, leveraging its specialized training data to provide relevant suggestions.
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Model Overview
The shopifyinterngrinder/sidekick-autocomplete-06b-sft-real model is a specialized language model, fine-tuned from the Qwen/Qwen3-0.6B base model. It utilizes the TRL library for Supervised Fine-Tuning (SFT) to adapt its capabilities for specific applications.
Key Training Details
This model underwent focused training on the shopifyinterngrinder/sidekick-autocomplete-data-real dataset, comprising 13,565 training examples and 1,508 validation examples. The training process involved:
- Base Model: Qwen/Qwen3-0.6B
- Epochs: 3
- Learning Rate: 2e-05
- Max Sequence Length: 512 tokens
- Precision: bf16
- Optimizer: adamw_torch_fused
Intended Use
Given its fine-tuning on a dedicated autocomplete dataset, this model is primarily designed for tasks requiring efficient and accurate autocomplete suggestions. Its relatively small size (0.8B parameters) combined with specialized training makes it suitable for integration into applications where quick, context-aware completions are crucial.