Damilya/qwen3-4b-kazakh-lora

TEXT GENERATIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:4BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 27, 2026License:cc-by-nc-4.0Architecture:Transformer Open Weights Gated Featherless Exclusive Cold

Damilya/qwen3-4b-kazakh-lora is a 4 billion parameter language model, fine-tuned from Qwen3-4B-Instruct-2507 using LoRA. This model is specifically optimized for Kazakh-language restaurant voice ordering, improving fidelity and menu-context faithfulness compared to its base model. It is designed for non-commercial use under a CC BY-NC 4.0 license.

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Model Overview

Damilya/qwen3-4b-kazakh-lora is a specialized language model based on the Qwen3-4B-Instruct-2507 architecture. It leverages LoRA (Low-Rank Adaptation) for fine-tuning, resulting in a 4 billion parameter model with a context length of 32768 tokens. The primary focus of this fine-tuning is to enhance its performance for specific applications.

Key Capabilities

  • Kazakh Language Fidelity: Significantly improves the accuracy and naturalness of Kazakh language processing.
  • Contextual Faithfulness: Addresses and fixes issues related to maintaining context, particularly within menu-driven interactions.
  • Restaurant Voice Ordering: Specifically optimized for use cases involving voice ordering in restaurant environments.

Differentiators

This model stands out due to its targeted fine-tuning for the Kazakh language and its application in a niche domain like restaurant voice ordering. Unlike general-purpose LLMs, it provides enhanced performance and reliability for this specific use case by improving language fidelity and ensuring context-aware responses.

Licensing

The fine-tuned model operates under a CC BY-NC 4.0 (non-commercial) license, while its base model, Qwen3-4B-Instruct-2507, is distributed under Apache 2.0.