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")# pip install -U transformers accelerate # 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 pytorch_model.bin from alisawuffles/roberta-large-wanli: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/alisawuffles/roberta-large-wanli/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://alisawuffles/roberta-large-wanli@refs/pr/2/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/alisawuffles/roberta-large-wanli/resolve/refs%2Fpr%2F2/pytorch_model.bin
1.42 GB
- Xet hash:
- 521983bd8d764f9c9d65741d182beea2a17431f80397eeb1c02eda92d78483d9
- Size of remote file:
- 1.42 GB
- SHA256:
- 3e566b4b84695dab9b4a9aa3548ee21b6f63df82abfaf623b3df3dd694a9fa9f
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