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title: README | |
emoji: ⚡ | |
colorFrom: blue | |
colorTo: green | |
sdk: static | |
pinned: false | |
# MLX Vision | |
A community org for model weights compatible with `mlxim` powered by MLX. | |
GitHub link: https://github.com/riccardomusmeci/mlx-image | |
These are weights converted from timm/torchvision and ready to be used. | |
## How to install | |
``` | |
pip install mlx-image | |
``` | |
## Models | |
To load a model with pre-trained weights: | |
```python | |
from mlxim.model import create_model | |
# loading weights from HuggingFace (https://huggingface.co./mlx-vision/resnet18-mlxim) | |
model = create_model("resnet18") # pretrained weights loaded from HF | |
# loading weights from another HuggingFace model | |
model = create_model("resnet18", weights="hf://repo_id/filename") | |
# loading weights from local file | |
model = create_model("resnet18", weights="path/to/resnet18/model.safetensors") | |
``` | |
## ImageNet-1K Results | |
Go to https://github.com/riccardomusmeci/mlx-image/blob/main/results/results-imagenet-1k.csv to check every model converted and its performance on ImageNet-1K with different settings. | |
> **TL;DR** performance is comparable to the original models from PyTorch implementations. | |