Instructions to use WYHu/fnd_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WYHu/fnd_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="WYHu/fnd_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("WYHu/fnd_bert") model = AutoModelForSequenceClassification.from_pretrained("WYHu/fnd_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5def750e5523b509c8c2f6c30549b7717bfe72759fc92b6760372c9c1c45df16
- Size of remote file:
- 433 MB
- SHA256:
- c2a239ab9b2551a493ab4453e65ff97d82d578a1c3ced29abd58e409b6af6912
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