upd md

README.md

@@ -11,6 +11,7 @@ tags:
 - music
 - art
 ---
+
 # Intro
 The Erhu Performance Technique Recognition Model is an audio analysis tool based on deep learning techniques, aiming to automatically distinguish different techniques in erhu performance. By deeply analyzing the acoustic characteristics of erhu music, the model is able to recognize 11 basic playing techniques, including split bow, pad bow, overtone, continuous bow, glissando, big glissando, strike bow, pizzicato, throw bow, staccato bow, vibrato, tremolo and vibrato. Through time-frequency conversion, feature extraction and pattern recognition, the model can accurately categorize the complex techniques of erhu performance, which provides an efficient technical support for music information retrieval, music education, and research on the art of erhu performance. The application of this model not only enriches the research in the field of music acoustics, but also opens up a new way for the inheritance and innovation of traditional music.
 
@@ -19,13 +20,13 @@ The Erhu Performance Technique Recognition Model is an audio analysis tool based
 
 ## Usage
 ```python
-from modelscope import snapshot_download
+from huggingface_hub import snapshot_download
 model_dir = snapshot_download("ccmusic-database/erhu_playing_tech")
 ```
 
 ## Maintenance
 ```bash
-git clone git@hf.co:ccmusic-database/erhu_playing_tech
+GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:ccmusic-database/erhu_playing_tech
 cd erhu_playing_tech
 ```