Instructions to use fasterinnerlooper/models-moved with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fasterinnerlooper/models-moved with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="fasterinnerlooper/models-moved")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("fasterinnerlooper/models-moved") model = AutoModelForMaskedLM.from_pretrained("fasterinnerlooper/models-moved", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0638828290b30b56b2eb2b5414b35fe7cd6a7f3628462697291f6081899a678a
- Size of remote file:
- 4.54 kB
- SHA256:
- b34a0d132b50d3e344baeced2ae9b4da86a0fe2bd798d5b3fb10277c1c5ab8b9
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