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 flax_model.msgpack from simonmun/Eyse_SentenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 369 MB
-
https://huggingface.co/simonmun/Eyse_SentenceClassification/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://simonmun/Eyse_SentenceClassification/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/simonmun/Eyse_SentenceClassification/resolve/main/flax_model.msgpack
369 MB
- Xet hash:
- d4d2240686e59dc7af10bf0b36170dc0514a307ca6f2a39f1c6ec0a18750a20d
- Size of remote file:
- 369 MB
- SHA256:
- 97a8bc10dab6b891bbe0d24540e85e67503cb8632f1043f8178447a7e638cd9b
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