webSLM: Fine-tuning, Compiling, and Running Domain-Specific Small Language Models Entirely in the Browser
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webSLM is an end-to-end pipeline for turning a general-purpose Small Language Model (SLM) into a domain-specialized assistant that runs 100% in the browser — no server, no API key, no inference cost, full offline capability after first load. This paper documents the complete lifecycle of a worked example, WebSLM-Medical-0.5B : (1) LoRA fine-tuning of Qwen2.5-0.5B-Instruct on a small domain dataset using a free Colab T4; (2) compilation and 4-bit quantization to a WebGPU model library via a…
1Key Takeaways
- webSLM is an end-to-end pipeline for turning a general-purpose Small Language Model (SLM) into a domain-specialized assistant that runs 100% in the browser — no server, no API key, no inference cost, full offline capability after first load.
- This paper documents the complete lifecycle of a worked example, WebSLM-Medical-0.5B : (1) LoRA fine-tuning of Qwen2.5-0.5B-Instruct on a small domain dataset using a free Colab T4; (2) compilation and 4-bit quantization to a WebGPU model library via a….
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that webSLM is an end-to-end pipeline for turning a general-purpose Small Language Model (SLM) into a domain-specialized assistant that runs 100% in the browser — no server, no API key, no inference cost, full offline capability after first load.
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