Srishtik/Qwen3-0.6B-slerp-order-dolly-codealpaca-metamath-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 26, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Srishtik/Qwen3-0.6B-slerp-order-dolly-codealpaca-metamath-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 2x faster fine-tuning. It is designed for general language tasks, leveraging its efficient training methodology for practical applications.

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Model Overview

This model, developed by Srishtik, is a Qwen3-0.6B variant that has been fine-tuned from the unsloth/Qwen3-0.6B base model. It incorporates a merged set of adapters, including those for slerp-order, dolly, codealpaca, and metamath, suggesting a broad range of capabilities across instruction following, coding, and mathematical reasoning.

Key Characteristics

  • Base Model: Qwen3-0.6B, a compact yet capable architecture.
  • Efficient Training: Fine-tuned with Unsloth, which facilitated a 2x faster training process.
  • Adapter Merging: Integrates multiple adapters (slerp-order, dolly, codealpaca, metamath) to enhance performance across diverse tasks.

Potential Use Cases

Given its multi-adapter fine-tuning, this model is potentially well-suited for:

  • Instruction Following: Benefiting from the Dolly adapter.
  • Code Generation & Understanding: Enhanced by the CodeAlpaca adapter.
  • Mathematical Problem Solving: Supported by the Metamath adapter.
  • General Language Tasks: Leveraging the base Qwen3 capabilities and efficient training.

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