Instructions to use korca/textfooler-roberta-base-rte-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use korca/textfooler-roberta-base-rte-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="korca/textfooler-roberta-base-rte-5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("korca/textfooler-roberta-base-rte-5") model = AutoModelForSequenceClassification.from_pretrained("korca/textfooler-roberta-base-rte-5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from korca/textfooler-roberta-base-rte-5: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/korca/textfooler-roberta-base-rte-5/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://korca/textfooler-roberta-base-rte-5/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/korca/textfooler-roberta-base-rte-5/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- a078c7a1990ff34206bd6cea8a21d924f9da00bbf90ac2b15d41673db39bf71d
- Size of remote file:
- 499 MB
- SHA256:
- 5bd7acf0f848b0846b4ef4b5bc2063e84ce3196b077e8d9a45292bf12dba64a8
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