Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use ghatgetanuj/roberta-large_cls_sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghatgetanuj/roberta-large_cls_sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ghatgetanuj/roberta-large_cls_sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ghatgetanuj/roberta-large_cls_sst2") model = AutoModelForSequenceClassification.from_pretrained("ghatgetanuj/roberta-large_cls_sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7eb15380836a69c47d489487e1e560c1cabd2107aa89ff0427124eec55671351
- Size of remote file:
- 1.42 GB
- SHA256:
- 99f5c495ea6d2f3a6eb5de6888094ffa5d3bf5cf9bd14a66ffc8cd9c28566b7c
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