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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonmun/COHA1990s") model = AutoModelForMaskedLM.from_pretrained("simonmun/COHA1990s", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from simonmun/COHA1990s: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/simonmun/COHA1990s/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://simonmun/COHA1990s/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/simonmun/COHA1990s/resolve/main/pytorch_model.bin
334 MB
- Xet hash:
- efeeeae2027d1d293e754cdc9349063607493b151e6d250c691455176e06fc0c
- Size of remote file:
- 334 MB
- SHA256:
- e9f3ca048f91ed42d59c2fedac69b97e7c1bc717964900b3f480342aab58695f
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