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 training_args.bin from simonmun/COHA1920s: direct link, hf CLI and curl.
- Browser
- Download file 1.52 kB
-
https://huggingface.co/simonmun/COHA1920s/resolve/main/training_args.bin
- Command line
-
hf download hf://simonmun/COHA1920s/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/simonmun/COHA1920s/resolve/main/training_args.bin
1.52 kB
- Xet hash:
- 015d8a8acb10a2071aa7e0a1c4861ede92864604c932947ffd25b5951f43d89d
- Size of remote file:
- 1.52 kB
- SHA256:
- bc2033f1e1671bcc042e9e0e693427ab89316dd0bb1a88c5acc90d1d42651b1f
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