Instructions to use bond005/wav2vec2-base-ru-birm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bond005/wav2vec2-base-ru-birm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bond005/wav2vec2-base-ru-birm")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("bond005/wav2vec2-base-ru-birm") model = AutoModelForCTC.from_pretrained("bond005/wav2vec2-base-ru-birm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from bond005/wav2vec2-base-ru-birm: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/bond005/wav2vec2-base-ru-birm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://bond005/wav2vec2-base-ru-birm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bond005/wav2vec2-base-ru-birm/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 922b12cf5acc9f877f29cf1b7a09f7915e85756f3ca74912e3d95627e5908eee
- Size of remote file:
- 378 MB
- SHA256:
- 2d4a32e967cd4e3e30856207f9b8e6cda3930b1c17a60879be4dd8ff94284bc1
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