Instructions to use alisawuffles/roberta-large-wanli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alisawuffles/roberta-large-wanli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alisawuffles/roberta-large-wanli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alisawuffles/roberta-large-wanli") model = AutoModelForSequenceClassification.from_pretrained("alisawuffles/roberta-large-wanli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from alisawuffles/roberta-large-wanli: direct link, hf CLI and curl.
- Browser
- Download file 2.67 kB
-
https://huggingface.co/alisawuffles/roberta-large-wanli/resolve/refs%2Fpr%2F2/training_args.bin
- Command line
-
hf download hf://alisawuffles/roberta-large-wanli@refs/pr/2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/alisawuffles/roberta-large-wanli/resolve/refs%2Fpr%2F2/training_args.bin
2.67 kB
- Xet hash:
- 4ab3ff7107ce1bb8df72ae9eacc0bd8671bd32ab3b73a86e037c89d6280c6e54
- Size of remote file:
- 2.67 kB
- SHA256:
- 74ec09eb0f61301520bf91d941806c5c4da5292c38fec5dcb1ab76e31633cb05
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