Instructions to use simonmun/COHA1900s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonmun/COHA1900s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simonmun/COHA1900s")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonmun/COHA1900s") model = AutoModelForMaskedLM.from_pretrained("simonmun/COHA1900s", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from simonmun/COHA1900s: direct link, hf CLI and curl.
- Browser
- Download file 1.78 kB
-
https://huggingface.co/simonmun/COHA1900s/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://simonmun/COHA1900s@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/simonmun/COHA1900s/resolve/refs%2Fpr%2F1/training_args.bin
1.78 kB
- Xet hash:
- feccf3a4ebfa8c48fe0ef7104fc378581e4c8dc1f67131d5c6cc03f621916c14
- Size of remote file:
- 1.78 kB
- SHA256:
- 5c557b959ddfe4a8e23121bd313e9a50ae27024c3a854b4c49680b6cd7a3a7c4
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