Metadata-Version: 2.4
Name: mt3-audio2midi
Version: 0.1.0
Summary: MT3 Music Transcription Library
Author-email: dummyjenil <dummyjenil@gmail.com>
Requires-Python: >=3.11
Requires-Dist: absl-py
Requires-Dist: cached-property
Requires-Dist: clu
Requires-Dist: fiddle>=0.2.5
Requires-Dist: flax
Requires-Dist: flax==0.10.7
Requires-Dist: gin-config
Requires-Dist: grain==0.2.0
Requires-Dist: immutabledict
Requires-Dist: jax>=0.4.16
Requires-Dist: jaxlib>=0.4.16
Requires-Dist: librosa
Requires-Dist: mir-eval
Requires-Dist: note-seq
Requires-Dist: numpy
Requires-Dist: optax
Requires-Dist: orbax-checkpoint>=0.5
Requires-Dist: pretty-midi
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: seqio==0.0.19
Requires-Dist: t5
Requires-Dist: tensorflow
Requires-Dist: tensorflow-cpu
Requires-Dist: tensorflow-datasets
Requires-Dist: tensorstore>=0.1.20
Description-Content-Type: text/markdown

```python
from huggingface_hub import hf_hub_download
from shutil import unpack_archive
from mt3_audio2midi import MT3
import nest_asyncio
nest_asyncio.apply()

unpack_archive(hf_hub_download("shethjenil/Audio2Midi_Models","mt3.zip"),"mt3_model",format="zip")
unpack_archive(hf_hub_download("shethjenil/Audio2Midi_Models","ismir2021.zip"),"ismir2021_model",format="zip")

mt3_model = MT3("mt3_model")
ismir2021_model = MT3("ismir2021_model","ismir2021")

mt3_model.predict(audio_path)
ismir2021_model.predict(audio_path)
```
