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 training_args.bin from simonmun/COHA2000s: direct link, hf CLI and curl.
- Browser
- Download file 1.23 kB
-
https://huggingface.co/simonmun/COHA2000s/resolve/main/training_args.bin
- Command line
-
hf download hf://simonmun/COHA2000s/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/simonmun/COHA2000s/resolve/main/training_args.bin
1.23 kB
- Xet hash:
- 6a5b1c4dce23c33331a177f443b33a9b320f72ccc2fb90e741eff34e194a8d5c
- Size of remote file:
- 1.23 kB
- SHA256:
- c00623244f49fb9b75b80ea7708ddd77202f7b33e811ab7634d29b4c6d52434c
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