Instructions to use brutusxu/roberta-large-finetuned-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brutusxu/roberta-large-finetuned-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="brutusxu/roberta-large-finetuned-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("brutusxu/roberta-large-finetuned-mnli") model = AutoModelForSequenceClassification.from_pretrained("brutusxu/roberta-large-finetuned-mnli") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
roberta-large-finetuned-mnli
roberta-large finetuned on mnli dataset https://huggingface.co/datasets/multi_nli
accuracy on val_match: 0.9013 accuracy on val_mismatch: 0.8995
usage
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained('roberta-large')
model = AutoModelForSequenceClassification
input_ids = tokenizer('I love English </s> I like English.',return_tensors='pt').input_ids
with torch.no_grad():
logits = model(input_ids).logits
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