Instructions to use ongknsro/ACARIS-DistilBERT_MLPUserEmbs-iter1-batchSize32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ongknsro/ACARIS-DistilBERT_MLPUserEmbs-iter1-batchSize32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ongknsro/ACARIS-DistilBERT_MLPUserEmbs-iter1-batchSize32")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, DistilBertForMulticlassSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ongknsro/ACARIS-DistilBERT_MLPUserEmbs-iter1-batchSize32") model = DistilBertForMulticlassSequenceClassification.from_pretrained("ongknsro/ACARIS-DistilBERT_MLPUserEmbs-iter1-batchSize32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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