Instructions to use ghatgetanuj/funnel-transformer-xlarge_cls_SentEval-CR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghatgetanuj/funnel-transformer-xlarge_cls_SentEval-CR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ghatgetanuj/funnel-transformer-xlarge_cls_SentEval-CR")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ghatgetanuj/funnel-transformer-xlarge_cls_SentEval-CR") model = AutoModelForSequenceClassification.from_pretrained("ghatgetanuj/funnel-transformer-xlarge_cls_SentEval-CR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 594a3fc4450da884960c257ac83e900db010cb66eed0a3624fa882e0213e706c
- Size of remote file:
- 1.77 GB
- SHA256:
- 7e75a35b21dfd4f560bd216f688df84281a96299db86f3748b8c58b6e1d84b9a
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