Text Generation
MLX
Merge
evolutionary-merge
darwin
darwin-v5
model-mri
reasoning
advanced-reasoning
chain-of-thought
thinking
qwen3.5
qwen
claude-opus
distillation
benchmark
open-source
apache-2.0
layer-wise-merge
coding-agent
tool-calling
long-context
quantized
Eval Results (legacy)
Instructions to use cudo528/Darwin-9B-Opus-mlx-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use cudo528/Darwin-9B-Opus-mlx-4bit 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("cudo528/Darwin-9B-Opus-mlx-4bit") 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 cudo528/Darwin-9B-Opus-mlx-4bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "cudo528/Darwin-9B-Opus-mlx-4bit" --prompt "Once upon a time"
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