How to use mgfrantz/deberta_v3_finetuned_predicting_effective_arguments with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mgfrantz/deberta_v3_finetuned_predicting_effective_arguments")
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mgfrantz/deberta_v3_finetuned_predicting_effective_arguments") model = AutoModelForSequenceClassification.from_pretrained("mgfrantz/deberta_v3_finetuned_predicting_effective_arguments", device_map="auto")
https://huggingface.co/mgfrantz/deberta_v3_finetuned_predicting_effective_arguments/resolve/main/tokenizer.json
hf download hf://mgfrantz/deberta_v3_finetuned_predicting_effective_arguments/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/mgfrantz/deberta_v3_finetuned_predicting_effective_arguments/resolve/main/tokenizer.json
