Instructions to use simonmun/Eyse_SentenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonmun/Eyse_SentenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="simonmun/Eyse_SentenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("simonmun/Eyse_SentenceClassification") model = AutoModelForSequenceClassification.from_pretrained("simonmun/Eyse_SentenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from simonmun/Eyse_SentenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 369 MB
-
https://huggingface.co/simonmun/Eyse_SentenceClassification/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://simonmun/Eyse_SentenceClassification@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/simonmun/Eyse_SentenceClassification/resolve/refs%2Fpr%2F1/pytorch_model.bin
369 MB
- Xet hash:
- 7a1e12a53c10a0654fa49f502cef74671a84d5ba91b89ec9af4f4f72c9893d12
- Size of remote file:
- 369 MB
- SHA256:
- ae614e99785c089357340089fb2d9ae3d058eed8d78298cdd5538fd58c71b194
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