Update README.md

README.md

@@ -1,3 +1,104 @@
 ---
 license: gpl-3.0
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+---
+license: gpl-3.0
+---
+MusicLang Predict model
+=======================
+
+![MusicLang logo](https://github.com/MusicLang/musiclang/blob/main/documentation/images/MusicLang.png?raw=true "MusicLang")
+
+
+This is the ONNX version (compatible with transformers.js) of MusicLang-4k.There is a unquantized and quantized version.
+MusicLang Predict is a model for creating original midi soundtracks with generative AI model.
+
+It can be used for different use cases :
+- Predict a new song from scratch (a fixed number of bars)
+- Continue a song from a prompt
+- Predict a new song from a template (see examples below)
+- Continue a song from a prompt and a template
+
+To solve template generation use cases,
+we provide an interface to create a template from an existing midi file.
+
+To make the prediction we have an inference package available here : [MusicLang Predict](https://github.com/MusicLang/musiclang_predict)
+which is based on the musiclang language : [MusicLang](https://huggingface.co/MusicLang).
+
+
+Installation
+------------
+
+Install the musiclang-predict package with pip :
+
+```bash
+pip install musiclang-predict
+```
+
+
+How to use ? 
+------------
+
+1. Create a new 8 bars song from scratch :
+
+```python
+from musiclang_predict import predict, MusicLangTokenizer
+from transformers import GPT2LMHeadModel
+
+# Load model and tokenizer
+model = GPT2LMHeadModel.from_pretrained('musiclang/musiclang-4k')
+tokenizer = MusicLangTokenizer('musiclang/musiclang-4k')
+soundtrack = predict(model, tokenizer, chord_duration=4, nb_chords=8)
+soundtrack.to_midi('song.mid', tempo=120, time_signature=(4, 4))
+```
+
+2. Or use an existing midi song as a song structure template :
+```python
+from musiclang_predict import midi_file_to_template, predict_with_template, MusicLangTokenizer
+from transformers import GPT2LMHeadModel
+
+# Load model and tokenizer
+model = GPT2LMHeadModel.from_pretrained('musiclang/musiclang-4k')
+tokenizer = MusicLangTokenizer('musiclang/musiclang-4k')
+
+template = midi_file_to_template('my_song.mid')
+soundtrack = predict_with_template(template, model, tokenizer)
+soundtrack.to_midi('song.mid', tempo=template['tempo'], time_signature=template['time_signature'])
+```
+
+See : [MusicLang templates](https://discovered-scabiosa-ea3.notion.site/Create-a-song-template-with-MusicLang-dfd8cad0a14b464fb3475c7fa19c1a82)
+For a full description of our template format.
+It's only a dictionary containing information for each chord of the song and some metadata like tempo.
+You can even create your own without using a base midi file !
+
+3. Or even use a prompt and a template to create a song
+
+```python
+from musiclang_predict import midi_file_to_template, predict_with_template, MusicLangTokenizer
+from transformers import GPT2LMHeadModel
+from musiclang import Score
+
+# Load model and tokenizer
+model = GPT2LMHeadModel.from_pretrained('musiclang/musiclang-4k')
+tokenizer = MusicLangTokenizer('musiclang/musiclang-4k')
+template = midi_file_to_template('my_song.mid')
+# Take the first chord of the template as a prompt
+prompt = Score.from_midi('my_prompt.mid', chord_range=(0, 4))
+soundtrack = predict_with_template(template, model, tokenizer, 
+                                   prompt=prompt,  # Prompt the model with a musiclang score
+                                   prompt_included_in_template=True  # To say the prompt score is included in the template
+                                   )
+soundtrack.to_midi('song.mid', tempo=template['tempo'], time_signature=template['time_signature'])
+```
+
+Contact us
+----------
+
+If you want to help shape the future of open source music generation,
+please contact [us](mailto:[email protected])
+
+License
+-------
+
+The MusicLang predict package (this package) and its associated models is licensed under the GPL-3.0 License.
+The MusicLang base language (musiclang package) is licensed under the BSD 3-Clause License.