Instructions to use simonmun/Lo_SentenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonmun/Lo_SentenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="simonmun/Lo_SentenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("simonmun/Lo_SentenceClassification") model = AutoModelForSequenceClassification.from_pretrained("simonmun/Lo_SentenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from simonmun/Lo_SentenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 369 MB
-
https://huggingface.co/simonmun/Lo_SentenceClassification/resolve/320c4fe8af1f099d713927a46de016af607e2ca7/flax_model.msgpack
- Command line
-
hf download hf://simonmun/Lo_SentenceClassification@320c4fe8af1f099d713927a46de016af607e2ca7/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/simonmun/Lo_SentenceClassification/resolve/320c4fe8af1f099d713927a46de016af607e2ca7/flax_model.msgpack
369 MB
- Xet hash:
- 97f5cb8f31e1d4605a08092d264c3f30b0df41d26e8b05300ff44a881b7a56b5
- Size of remote file:
- 369 MB
- SHA256:
- f0ca8fc56468d71e7d5399173228c5ddcc8d76af3e723e63d9b299ffc3cc2f82
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