Instructions to use anjleeg/roberta-base-finetuned-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anjleeg/roberta-base-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anjleeg/roberta-base-finetuned-cola")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anjleeg/roberta-base-finetuned-cola") model = AutoModelForSequenceClassification.from_pretrained("anjleeg/roberta-base-finetuned-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from anjleeg/roberta-base-finetuned-cola: direct link, hf CLI and curl.
- Browser
- Download file 249 MB
-
https://huggingface.co/anjleeg/roberta-base-finetuned-cola/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://anjleeg/roberta-base-finetuned-cola/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/anjleeg/roberta-base-finetuned-cola/resolve/main/pytorch_model.bin
249 MB
- Xet hash:
- c0e63ba65b5f6c4ef2d8b077a6e95c1f1873bf8789d76565ea7aa38ce01f6357
- Size of remote file:
- 249 MB
- SHA256:
- cfa810debbf86568b2ec4adcc5a5486c0d9e595cb9de06fcb554c022654dadde
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