Instructions to use BELLE-2/Belle-whisper-large-v3-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BELLE-2/Belle-whisper-large-v3-zh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="BELLE-2/Belle-whisper-large-v3-zh")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("BELLE-2/Belle-whisper-large-v3-zh") model = AutoModelForSpeechSeq2Seq.from_pretrained("BELLE-2/Belle-whisper-large-v3-zh") - Notebooks
- Google Colab
- Kaggle
why is the model so large?
2
#12 opened 11 months ago
by
WangBicheng
Adding `safetensors` variant of this model
1
#9 opened almost 2 years ago
by
SFconvertbot
Adding custom vocabularies to v3-zh model
#8 opened almost 2 years ago
by
MonoLeon
What's the decoder_start_token_id and eos_token_id used in training?
#7 opened almost 2 years ago
by
cqchangm
想得到更小的模型。。
1
#6 opened almost 2 years ago
by
xuxiaoshuo
模型文件中缺乏tokennizer.json文件,无法按照教程用ct2-transformer
1
#5 opened about 2 years ago
by
ouyangk
fix: add max length to config
#4 opened about 2 years ago
by
evshiron
如何支持添加标点符号?
3
#3 opened about 2 years ago
by
Yi0956
Adding `safetensors` variant of this model
#2 opened about 2 years ago
by
SFconvertbot
How to get text with timestamp?
2
#1 opened about 2 years ago
by
InYourmemOry