Instructions to use ragarwal/args-me-crossencoder-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ragarwal/args-me-crossencoder-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ragarwal/args-me-crossencoder-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ragarwal/args-me-crossencoder-v1") model = AutoModelForSequenceClassification.from_pretrained("ragarwal/args-me-crossencoder-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3dc8fba955f8706515e6ef6e502435b460dcdd7c782faf4fc1bd1149aac4611e
- Size of remote file:
- 499 MB
- SHA256:
- d1a5a3ec81f858878d31def76411a68cdf700e7102cc88f1a36145c36ae17e73
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