Instructions to use mrmorenom/BERT-3Class-SC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrmorenom/BERT-3Class-SC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrmorenom/BERT-3Class-SC")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrmorenom/BERT-3Class-SC") model = AutoModelForSequenceClassification.from_pretrained("mrmorenom/BERT-3Class-SC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1de601938df438adba869cb5e2eecabe4dfd2915ff83cfe85e3f38117c45f79b
- Size of remote file:
- 473 MB
- SHA256:
- a91c68aa803515c3aa8fdcfaea23b50c5bcd4d19faec9aad4e6e2a028029c87c
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