huggingface / huggingface/blog
fails on 'processor = Wav2Vec2ProcessorWithLM.from_pretrained("patrickvonplaten/wav2vec2-base-100h-with-lm")'
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Description
the following step in 'Boosting Wav2Vec2 with n-grams in 🤗 Transformers' colab example fails
```
from transformers import Wav2Vec2ProcessorWithLM
processor = Wav2Vec2ProcessorWithLM.from_pretrained("patrickvonplaten/wav2vec2-base-100h-with-lm")
```
with the following error:
```
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
in ()
1 from transformers import Wav2Vec2ProcessorWithLM
2
----> 3 processor = Wav2Vec2ProcessorWithLM.from_pretrained("patrickvonplaten/wav2vec2-base-100h-with-lm")
1 frames
/usr/local/lib/python3.7/dist-packages/transformers/file_utils.py in requires_backends(obj, backends)
820 name = obj.__name__ if hasattr(obj, "__name__") else obj.__class__.__name__
821 if not all(BACKENDS_MAPPING[backend][0]() for backend in backends):
--> 822 raise ImportError("".join([BACKENDS_MAPPING[backend][1].format(name) for backend in backends]))
823
824
ImportError:
Wav2Vec2ProcessorWithLM requires the pyctcdecode library but it was not found in your environment. You can install it with pip:
`pip install pyctcdecode`
---------------------------------------------------------------------------
NOTE: If your import is failing due to a missing package, you can
manually install dependencies using either !pip or !apt.
To view examples of installing some common dependencies, click the
"Open Examples" button below.
---------------------------------------------------------------------------
```
Although **pyctcdecode** and **kenlm** installation is successful.
Contributor guide
No contributing guide indexed for this repository
Research direction
Start with the “Boosting Wav2Vec2 with n-grams in 🤗 Transformers” Colab example and reproduce the Wav2Vec2ProcessorWithLM.from_pretrained step after the documented pyctcdecode and kenlm installations. Check the dependency-installation and processor-loading cells; done means the example loads the processor without the reported missing-library error.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- documentation, machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100