Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2-bert
Generated from Trainer
Instructions to use Bajiyo/w2v-bert-2_7_datasets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bajiyo/w2v-bert-2_7_datasets with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Bajiyo/w2v-bert-2_7_datasets")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Bajiyo/w2v-bert-2_7_datasets") model = AutoModelForCTC.from_pretrained("Bajiyo/w2v-bert-2_7_datasets", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Bajiyo/w2v-bert-2_7_datasets: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/Bajiyo/w2v-bert-2_7_datasets/resolve/main/training_args.bin
- Command line
-
hf download hf://Bajiyo/w2v-bert-2_7_datasets/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Bajiyo/w2v-bert-2_7_datasets/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 3a803df5412d23ea2fb6dce4dd180921d022e3dce71a3632ae427694499775e8
- Size of remote file:
- 5.18 kB
- SHA256:
- 69331e7dd9f30cb5ab9f74c65224b6726250445bfaf6ac300a8e04f65d89e680
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