Instructions to use liamliang/demographics_race with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liamliang/demographics_race with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="liamliang/demographics_race")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("liamliang/demographics_race") model = AutoModelForSequenceClassification.from_pretrained("liamliang/demographics_race", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from liamliang/demographics_race: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/liamliang/demographics_race/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://liamliang/demographics_race/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/liamliang/demographics_race/resolve/main/flax_model.msgpack
438 MB
- Xet hash:
- 7c34877fa0e7a65e6556b2ca67ead473d910daf3f70666f01f6547317e0927c8
- Size of remote file:
- 438 MB
- SHA256:
- c4ddb15422d6484b2269c07ee20b460288bbf70fafd9221db43d40922567f7d0
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