by0101/qwen3-4b-star-qlora-r16-v2-merged
TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Sep 6, 2026Architecture:Transformer Featherless Exclusive Cold
by0101/qwen3-4b-star-qlora-r16-v2-merged is a 4 billion parameter causal language model, fine-tuned from Qwen/Qwen3-4B. This model is specifically optimized for STAR (Situation, Task, Action, Result) interview answer analysis. It was trained using QLoRA/LoRA methods, with the adapter merged into the base model for direct loading, and supports a 32768 token context length.
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Model Overview
This model, by0101/qwen3-4b-star-qlora-r16-v2-merged, is a 4 billion parameter causal language model derived from Qwen/Qwen3-4B. It has been fine-tuned using QLoRA/LoRA techniques, with the adapter weights merged directly into the base model. This allows for straightforward loading and usage without requiring PEFT.
Key Capabilities
- Specialized Task: Primarily designed for STAR (Situation, Task, Action, Result) interview answer analysis.
- Base Architecture: Built upon the robust Qwen3-4B model.
- Direct Loading: The LoRA adapter is merged, enabling direct loading of the model for text generation tasks.
- Context Length: Supports a substantial context window of 32768 tokens.
Good For
- Analyzing and processing interview responses structured around the STAR method.
- Applications requiring a specialized language model for specific HR or recruitment-related text analysis.
- Developers seeking a pre-merged, fine-tuned Qwen3-4B variant for immediate deployment in text generation pipelines.