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 pytorch_model.bin from simonmun/Lo_SentenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 369 MB
-
https://huggingface.co/simonmun/Lo_SentenceClassification/resolve/e4d1c2c03809e7c5f65bc47fa48f0dcf7100599e/pytorch_model.bin
- Command line
-
hf download hf://simonmun/Lo_SentenceClassification@e4d1c2c03809e7c5f65bc47fa48f0dcf7100599e/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/simonmun/Lo_SentenceClassification/resolve/e4d1c2c03809e7c5f65bc47fa48f0dcf7100599e/pytorch_model.bin
369 MB
- Xet hash:
- a4dae20a197056973f9285594ecd2912f14085060a80c17a2c6906376f5110cd
- Size of remote file:
- 369 MB
- SHA256:
- 9afa21f135a578c399d07c6c807e247874128f2e2f26de027496e926293bad01
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