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:
- c37e9dc15b7080df54a1b9f9a09ef6c9fbcf8938ce8fa255f194a83b8b7750c0
- Size of remote file:
- 3.12 kB
- SHA256:
- c0c7e667da790969569f0a2ddd711b8553cf0da1cc48228bf9a779335b974684
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