Instructions to use ModelTC/roberta-base-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/roberta-base-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/roberta-base-cola")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/roberta-base-cola") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/roberta-base-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from ModelTC/roberta-base-cola: direct link, hf CLI and curl.
- Browser
- Download file 997 MB
-
https://huggingface.co/ModelTC/roberta-base-cola/resolve/main/optimizer.pt
- Command line
-
hf download hf://ModelTC/roberta-base-cola/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/ModelTC/roberta-base-cola/resolve/main/optimizer.pt
997 MB
- Xet hash:
- 69af6f258e14d501d478a6ea94af35611412074d56d28a5b9760ff44f6e60796
- Size of remote file:
- 997 MB
- SHA256:
- 1ce93ed6b663738f27839273e760adec72615c032f231c691737639c0810f69c
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