# Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("kornesh/xlm-roberta-base")
model = AutoModel.from_pretrained("kornesh/xlm-roberta-base", device_map="auto")Quick Links
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Check out the documentation for more information.
Converted for Tensorflow
!pip install transformers sentencepiece
from transformers import TFAutoModel, AutoTokenizer
name = "xlm-roberta-base"
model = TFAutoModel.from_pretrained(name, from_pt=True)
tokenizer = AutoTokenizer.from_pretrained(name)
model.save_pretrained("local-xlm-roberta-base")
tokenizer.save_pretrained("local-xlm-roberta-base")
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="kornesh/xlm-roberta-base")