Instructions to use ITG/wav2vec2-large-xlsr-gl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ITG/wav2vec2-large-xlsr-gl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ITG/wav2vec2-large-xlsr-gl")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ITG/wav2vec2-large-xlsr-gl") model = AutoModelForCTC.from_pretrained("ITG/wav2vec2-large-xlsr-gl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ITG/wav2vec2-large-xlsr-gl: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/ITG/wav2vec2-large-xlsr-gl/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ITG/wav2vec2-large-xlsr-gl/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ITG/wav2vec2-large-xlsr-gl/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- 7aa2c603b53d02dbe4e605df381fcb611fc1c4e427e65a969a07079818abd7bc
- Size of remote file:
- 1.26 GB
- SHA256:
- 939fe6b3ca3a3f8ae16c48f6e2d5f9afda518f65e7ab51f7bc3e217fa18d61b7
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