Text Generation
MLX
English
qwen3
mlx-lm
lora
qlora
medical
triage
local-first
edge-ai
apple-silicon
unified-memory
low-token
Instructions to use loll070303/one-apple-a-day-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use loll070303/one-apple-a-day-mlx 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("loll070303/one-apple-a-day-mlx") 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 loll070303/one-apple-a-day-mlx with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "loll070303/one-apple-a-day-mlx" --prompt "Once upon a time"
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# One Apple a Day MLX
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[](https://huggingface.co/loll070303/one-apple-a-day-mlx)
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[](https://huggingface.co/loll070303/one-apple-a-day-mlx)
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This repository contains a lightweight LoRA adapter for `mlx-community/Qwen3.5-4B-MLX-4bit`, fine-tuned for **local MLX inference** and **low-token medical triage-style responses**.
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