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 training_args.bin from simonmun/COHA1990s: direct link, hf CLI and curl.
- Browser
- Download file 1.78 kB
-
https://huggingface.co/simonmun/COHA1990s/resolve/main/training_args.bin
- Command line
-
hf download hf://simonmun/COHA1990s/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/simonmun/COHA1990s/resolve/main/training_args.bin
1.78 kB
- Xet hash:
- fef867379a116bdb22f136a956bed1a36af66b7904348901b5554504a389b83b
- Size of remote file:
- 1.78 kB
- SHA256:
- f25191ca88c7d1c3e13b8ceffd8ccb6503c943978776ee66211c153a4ce0f60a
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