Instructions to use microsoft/wavlm-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/wavlm-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="microsoft/wavlm-large")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("microsoft/wavlm-large") model = AutoModel.from_pretrained("microsoft/wavlm-large") - Notebooks
- Google Colab
- Kaggle
weights warning/error
#4
by Mordehay - opened
I got the following warning:
Some weights of the model checkpoint at microsoft/wavlm-large were not used when initializing WavLMModel: ['encoder.pos_conv_embed.conv.weight_g', 'encoder.pos_conv_embed.conv.weight_v']
- This IS expected if you are initializing WavLMModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing WavLMModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
when I tried to run this code:
from transformers import pipeline
pipe = pipeline("feature-extraction", model="microsoft/wavlm-large") Copy # Load model directly
from transformers import AutoProcessor, AutoModel
processor = AutoProcessor.from_pretrained("microsoft/wavlm-large")
model = AutoModel.from_pretrained("microsoft/wavlm-large")