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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FacebookAI/roberta-large-mnli") model = AutoModelForSequenceClassification.from_pretrained("FacebookAI/roberta-large-mnli", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from FacebookAI/roberta-large-mnli: direct link, hf CLI and curl.
- Browser
- Download file 1.43 GB
-
https://huggingface.co/FacebookAI/roberta-large-mnli/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://FacebookAI/roberta-large-mnli/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/FacebookAI/roberta-large-mnli/resolve/main/pytorch_model.bin
1.43 GB
- Xet hash:
- 8a8aedfa9373273863fbcabbcb0504bc62263fb25db477f9793422752f8cd70a
- Size of remote file:
- 1.43 GB
- SHA256:
- 5a7be848f7dd81983947515b3209f9b4960d06eac3dde368b1aa7a4b8c0b08b7
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