Instructions to use korca/textfooler-roberta-base-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use korca/textfooler-roberta-base-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="korca/textfooler-roberta-base-sst2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("korca/textfooler-roberta-base-sst2") model = AutoModelForSequenceClassification.from_pretrained("korca/textfooler-roberta-base-sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from korca/textfooler-roberta-base-sst2: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/korca/textfooler-roberta-base-sst2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://korca/textfooler-roberta-base-sst2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/korca/textfooler-roberta-base-sst2/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- b1f3e305f144220c85145adc584a97e8ac81c3ff52bb51b22432d8a5c9b1d1e7
- Size of remote file:
- 499 MB
- SHA256:
- 17d0987b83df2174e9d43f0a821e7df63ce306978d601aceac82f2d78dcc945d
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