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")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonmun/COHA1850s") model = AutoModelForMaskedLM.from_pretrained("simonmun/COHA1850s") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49fc78a98186a526bf3383a9d064291f4ab9bbfdd3fcb0c0480b1f8730a95539
- Size of remote file:
- 334 MB
- SHA256:
- 088d619ce4491bde3f70a8797bbc49ad4560e95a3d61d927f2601ce96461a5a0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.