Automatic Speech Recognition
Transformers
PyTorch
English
bert
text-classification
exbert
autotrain-compatible
Instructions to use danielsc/bert_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielsc/bert_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="danielsc/bert_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("danielsc/bert_test") model = AutoModelForSequenceClassification.from_pretrained("danielsc/bert_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca9b1e319d1f4604153908c235a9159c78351b503a46da84446d0b4f2142d31c
- Size of remote file:
- 433 MB
- SHA256:
- 0183382f883ddaef60d7c93bb59d70cc75a9905e12b9264d8cd9cffffb421c9c
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