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 model.safetensors 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/model.safetensors
- Command line
-
hf download hf://simonmun/Eyse_SentenceClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/simonmun/Eyse_SentenceClassification/resolve/refs%2Fpr%2F1/model.safetensors
369 MB
- Xet hash:
- f5a3db92d53da2d38703a4a45f4ed209668379dbb89ef72022c2d0d3ac642bc7
- Size of remote file:
- 369 MB
- SHA256:
- 9864a88f0ccc96ff7c6f2f9b37db38d439b66807e2e74cab23c4d5a2914907c9
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