Instructions to use HiAmNear/cafebert-ViFE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiAmNear/cafebert-ViFE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HiAmNear/cafebert-ViFE")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HiAmNear/cafebert-ViFE") model = AutoModelForSequenceClassification.from_pretrained("HiAmNear/cafebert-ViFE") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b3a9492856214c81cfb9f3e5d85225fe5836991140eace436d3977545f6c2d0
- Size of remote file:
- 5.3 kB
- SHA256:
- a68a9403af5b179e3b07610e3bdc2f379f943c6b6adf68d8636afeed754a7b70
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