Instructions to use nmb-paperspace-hf/roberta-base-finetuned-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nmb-paperspace-hf/roberta-base-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nmb-paperspace-hf/roberta-base-finetuned-cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nmb-paperspace-hf/roberta-base-finetuned-cola") model = AutoModelForSequenceClassification.from_pretrained("nmb-paperspace-hf/roberta-base-finetuned-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nmb-paperspace-hf/roberta-base-finetuned-cola: direct link, hf CLI and curl.
- Browser
- Download file 2.74 kB
-
https://huggingface.co/nmb-paperspace-hf/roberta-base-finetuned-cola/resolve/main/training_args.bin
- Command line
-
hf download hf://nmb-paperspace-hf/roberta-base-finetuned-cola/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nmb-paperspace-hf/roberta-base-finetuned-cola/resolve/main/training_args.bin
2.74 kB
- Xet hash:
- 25f3ff8ad8727622d4ae7d0fb3ab8538c77bf190d37a542be70d661d272a53d0
- Size of remote file:
- 2.74 kB
- SHA256:
- 2e6f9b978fd1fb0d368a10f486ff88a5fade11a2e9377d6e19cb88711dd42ab9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.