Srishtik/Qwen3-0.6B-slerp-FIXED-3-adapters-merged-2

TEXT GENERATIONPricing:Input $0.04 / Cached $0.008 / Output $0.08Concurrent Unit Cost:1Model Size:0.8BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 28, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Srishtik/Qwen3-0.6B-slerp-FIXED-3-adapters-merged-2 is a 0.8 billion parameter Qwen3 model developed by Srishtik, fine-tuned from unsloth/Qwen3-0.6B. This model was trained using Unsloth, enabling faster training times. It is designed for general language tasks, leveraging the Qwen3 architecture for efficient performance.

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Model Overview

Srishtik/Qwen3-0.6B-slerp-FIXED-3-adapters-merged-2 is a 0.8 billion parameter language model based on the Qwen3 architecture. Developed by Srishtik, this model was fine-tuned from the unsloth/Qwen3-0.6B base model.

Key Characteristics

  • Architecture: Qwen3
  • Parameter Count: 0.8 billion parameters
  • Training Method: Fine-tuned using Unsloth, which facilitated a 2x faster training process.
  • License: Apache-2.0, allowing for broad usage and distribution.

Intended Use Cases

This model is suitable for a variety of general natural language processing tasks where a compact yet capable model is required. Its efficient training via Unsloth suggests potential benefits for applications prioritizing faster iteration and deployment. Developers can leverage its Qwen3 foundation for tasks such as text generation, summarization, and question answering, particularly in environments where computational resources are a consideration.

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