Instructions to use laboyle1/distilbert-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use laboyle1/distilbert-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="laboyle1/distilbert-finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("laboyle1/distilbert-finetuned") model = AutoModelForMaskedLM.from_pretrained("laboyle1/distilbert-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a53b594196957c9a5c8f5e5bd5f3bbf65d7984ef41a34a493549f456cfa28d94
- Size of remote file:
- 3.18 kB
- SHA256:
- 38b4c5515495f12e2545911b872f5af4b3e924792ec053db32e407feaf93476d
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