Instructions to use lukecarlate/andlabtest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukecarlate/andlabtest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lukecarlate/andlabtest")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lukecarlate/andlabtest") model = AutoModelForMaskedLM.from_pretrained("lukecarlate/andlabtest") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab93afa65ca5437f7ec1f3b9ef8345683d49b950b39d2a74301868e62d263357
- Size of remote file:
- 3.96 kB
- SHA256:
- 6604dcfee7e236e7996b3c19364872b9aee4934bf5f464aaae815afcfda7a7c7
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