Instructions to use CALM-Lab-Purdue/distilbert-base-uncased-finetuned-quantifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CALM-Lab-Purdue/distilbert-base-uncased-finetuned-quantifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="CALM-Lab-Purdue/distilbert-base-uncased-finetuned-quantifier")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CALM-Lab-Purdue/distilbert-base-uncased-finetuned-quantifier") model = AutoModelForMaskedLM.from_pretrained("CALM-Lab-Purdue/distilbert-base-uncased-finetuned-quantifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 928234ba0f045637b22bf6ac5033a6b424d52abd3a71f15fcc8b59d4115b5210
- Size of remote file:
- 268 MB
- SHA256:
- 4edf1295eac73f1ee49ebd00f9566bb3243349d39b43cb67daed22bd64b49451
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