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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonmun/COHA2000s") model = AutoModelForMaskedLM.from_pretrained("simonmun/COHA2000s", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from simonmun/COHA2000s: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/simonmun/COHA2000s/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://simonmun/COHA2000s@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/simonmun/COHA2000s/resolve/refs%2Fpr%2F1/pytorch_model.bin
336 MB
- Xet hash:
- bf46f81d77671d74097b91dc4cc9e31d3c441a2eb0f7974e3b1a73ba1cf348d0
- Size of remote file:
- 336 MB
- SHA256:
- d41cc72a09b33536e4a4bc1d03d7ff795638fe8df7b9c129f72a71ae8c35b271
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