Instructions to use simonmun/COHA1920s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonmun/COHA1920s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simonmun/COHA1920s")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonmun/COHA1920s") model = AutoModelForMaskedLM.from_pretrained("simonmun/COHA1920s", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from simonmun/COHA1920s: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/simonmun/COHA1920s/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://simonmun/COHA1920s@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/simonmun/COHA1920s/resolve/refs%2Fpr%2F1/pytorch_model.bin
336 MB
- Xet hash:
- bfb755c8bc0cf9af55ebd7ce292f2f742e7f6b57f60140cc205d9f7f6a9f0c8d
- Size of remote file:
- 336 MB
- SHA256:
- bac1cda6b433c3ec0483bba6f837cf8e47c1470b327488cc0989d133a3a271a6
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