Instructions to use simonmun/COHA1980s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonmun/COHA1980s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simonmun/COHA1980s")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonmun/COHA1980s") model = AutoModelForMaskedLM.from_pretrained("simonmun/COHA1980s", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from simonmun/COHA1980s: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/simonmun/COHA1980s/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://simonmun/COHA1980s/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/simonmun/COHA1980s/resolve/main/pytorch_model.bin
334 MB
- Xet hash:
- 8279509aaaea8975b00d7a0554a967c2df8bb5e07c0e79075f3cec0ca3861655
- Size of remote file:
- 334 MB
- SHA256:
- 732ae4e13a60ed55159843ad6d40d8b158e4d1a861aa3e241ef2ccba2f431c24
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