Instructions to use contemmcm/1a7d904346e7c4adfb1de13434e74811 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use contemmcm/1a7d904346e7c4adfb1de13434e74811 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="contemmcm/1a7d904346e7c4adfb1de13434e74811")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("contemmcm/1a7d904346e7c4adfb1de13434e74811") model = AutoModelForSequenceClassification.from_pretrained("contemmcm/1a7d904346e7c4adfb1de13434e74811", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
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