Text Classification
Transformers
Safetensors
xlm-roberta
finetuning
xnli
mnli
text-embeddings-inference
Instructions to use ajayat/xlm-roberta-large-xnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ajayat/xlm-roberta-large-xnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ajayat/xlm-roberta-large-xnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ajayat/xlm-roberta-large-xnli") model = AutoModelForSequenceClassification.from_pretrained("ajayat/xlm-roberta-large-xnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9954c260a8492733f8957f63c3f0a91752941a18a8363b8484babd596620f0b3
- Size of remote file:
- 17.1 MB
- SHA256:
- 08abe94afda983bc797a5ea27aeed00680982397c52a795adfaf06328d4f2581
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.