Instructions to use Cheatham/xlm-roberta-large-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cheatham/xlm-roberta-large-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cheatham/xlm-roberta-large-finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cheatham/xlm-roberta-large-finetuned") model = AutoModelForSequenceClassification.from_pretrained("Cheatham/xlm-roberta-large-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Cheatham/xlm-roberta-large-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 2.24 GB
-
https://huggingface.co/Cheatham/xlm-roberta-large-finetuned/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Cheatham/xlm-roberta-large-finetuned/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Cheatham/xlm-roberta-large-finetuned/resolve/main/pytorch_model.bin
2.24 GB
- Xet hash:
- e0f7c0291f1a2c39b3ab0bb3d21986c496989f440da6994dd9c7dd32a1307ce2
- Size of remote file:
- 2.24 GB
- SHA256:
- de524044127c0c1cbc9bf676e7b1bc4d641bf426847965eb95dc39631216c195
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