Instructions to use simonmun/COHA2000s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonmun/COHA2000s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simonmun/COHA2000s")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonmun/COHA2000s") model = AutoModelForMaskedLM.from_pretrained("simonmun/COHA2000s") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e73ce046481d7185e50470b4bcde73409ff1fb017c018cdf7e1e5c025f8f7c0f
- Size of remote file:
- 334 MB
- SHA256:
- fb2bce475760250c3cf52f0aa8d523cc13413fb03190c284d3c0591eea001350
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