Instructions to use cagataydev/qwen3-strands-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use cagataydev/qwen3-strands-adapter with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("cagataydev/qwen3-strands-adapter") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use cagataydev/qwen3-strands-adapter with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "cagataydev/qwen3-strands-adapter" --prompt "Once upon a time"
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README.md
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## 🙏 Acknowledgments
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- Built with [Strands Agents SDK](https://github.com/strands-agents/
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- Base model: [Qwen3-1.7B-4bit](https://huggingface.co/mlx-community/Qwen3-1.7B-4bit)
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- Training framework: [MLX](https://github.com/ml-explore/mlx)
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## 🔗 Links
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- **Strands SDK:** https://github.com/strands-agents/
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- **Strands MLX:** https://github.com/cagataycali/strands-mlx
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- **Base Model:** https://huggingface.co/mlx-community/Qwen3-1.7B-4bit
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## 🙏 Acknowledgments
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- Built with [Strands Agents SDK](https://github.com/strands-agents/sdk-python)
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- Base model: [Qwen3-1.7B-4bit](https://huggingface.co/mlx-community/Qwen3-1.7B-4bit)
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- Training framework: [MLX](https://github.com/ml-explore/mlx)
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## 🔗 Links
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- **Strands SDK:** https://github.com/strands-agents/sdk-python
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- **Strands MLX:** https://github.com/cagataycali/strands-mlx
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- **Base Model:** https://huggingface.co/mlx-community/Qwen3-1.7B-4bit
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