Instructions to use simonmun/COHA1990s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonmun/COHA1990s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simonmun/COHA1990s")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonmun/COHA1990s") model = AutoModelForMaskedLM.from_pretrained("simonmun/COHA1990s") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d139cbf3bff3575a8f4fcb6cbca4d5803ebc66e9189bb05139d5c6d682871024
- Size of remote file:
- 334 MB
- SHA256:
- 6f91d632c1f2da48e45b7e2aff4de6e6e19b31f4150adf7e1f28c65e1674382c
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