Instructions to use simonmun/COHA1990s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonmun/COHA1990s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simonmun/COHA1990s")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simonmun/COHA1990s") model = AutoModelForMaskedLM.from_pretrained("simonmun/COHA1990s", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from simonmun/COHA1990s: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/simonmun/COHA1990s/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://simonmun/COHA1990s@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/simonmun/COHA1990s/resolve/refs%2Fpr%2F1/flax_model.msgpack
334 MB
- Xet hash:
- d139cbf3bff3575a8f4fcb6cbca4d5803ebc66e9189bb05139d5c6d682871024
- Size of remote file:
- 334 MB
- SHA256:
- 6f91d632c1f2da48e45b7e2aff4de6e6e19b31f4150adf7e1f28c65e1674382c
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