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:
- ec237af07f99af7ec269140dcc2c3c5c38e8c6d1c61c5b65d5904ebe9aa837e2
- Size of remote file:
- 439 MB
- SHA256:
- bdb4c0e989c201519031401a5b8bb7ad739cf766f43accc835388b5e0616f642
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