How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "shopifyinterngrinder/sidekick-autocomplete"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "shopifyinterngrinder/sidekick-autocomplete",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/shopifyinterngrinder/sidekick-autocomplete
Quick Links

shopifyinterngrinder/sidekick-autocomplete

Fine-tuned from Qwen/Qwen3-4B using TRL SFT.

Training Details

Parameter Value
Base Model Qwen/Qwen3-4B
Dataset shopifyinterngrinder/sidekick-autocomplete-data @ main
Training Examples 900
Validation Examples 101
Epochs 3
Learning Rate 2e-05
Batch Size (per device) 1
Gradient Accumulation 2
Max Sequence Length 512
Precision bf16
Optimizer adamw_torch_fused
Warmup Steps 50
Weight Decay 0.01
LR Scheduler cosine
Packing Enabled
Dataset Format chat

Framework Versions

Library Version
Transformers 4.57.6
TRL 0.29.0
PyTorch 2.8.0+cu128
Datasets 3.6.0
Accelerate 1.13.0
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