Instructions to use simonmun/COHA1850s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonmun/COHA1850s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simonmun/COHA1850s")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonmun/COHA1850s") model = AutoModelForMaskedLM.from_pretrained("simonmun/COHA1850s", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from simonmun/COHA1850s: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/simonmun/COHA1850s/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://simonmun/COHA1850s/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/simonmun/COHA1850s/resolve/main/pytorch_model.bin
336 MB
- Xet hash:
- 07e8821859573dc660513a6733f12981eec921f93ac9ee08dec25422b9bcafaf
- Size of remote file:
- 336 MB
- SHA256:
- b5dfbfe6265c0810fac16ee2b97b5319121af54bb3849f5a3eaaa6e58bbe9eb7
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