Text Classification
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
roberta
autogenerated-modelcard
text-embeddings-inference
Instructions to use FacebookAI/roberta-large-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/roberta-large-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FacebookAI/roberta-large-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FacebookAI/roberta-large-mnli") model = AutoModelForSequenceClassification.from_pretrained("FacebookAI/roberta-large-mnli") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e61a1c52a97246a26770960a5a4f2fd9444e8492d00347239dbe526350a21f6
- Size of remote file:
- 1.42 GB
- SHA256:
- 3268be4442922e0996ec369490b00b70ce419c678f1bf5f3f8b8f290b677bd7f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.