Instructions to use jamesdborin/Roberta-Large-RTE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jamesdborin/Roberta-Large-RTE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jamesdborin/Roberta-Large-RTE")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jamesdborin/Roberta-Large-RTE") model = AutoModelForSequenceClassification.from_pretrained("jamesdborin/Roberta-Large-RTE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
acde403 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:6d6ba03e261199bee0857a3254ff4a840593d0e5630e24fa207d4398e3fb063a
size 1421587189
|