# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("bertin-project/bertin-base-random-exp-512seqlen")
model = AutoModelForMaskedLM.from_pretrained("bertin-project/bertin-base-random-exp-512seqlen")Quick Links
This is a RoBERTa-base model trained from scratch in Spanish.
The training dataset is mc4 subsampling documents to a total of about 50 million examples. Sampling is random. This model continued training from sequence length 128 using 20.000 steps for length 512.
Please see our main card for more information.
This is part of the Flax/Jax Community Week, organised by HuggingFace and TPU usage sponsored by Google.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bertin-project/bertin-base-random-exp-512seqlen")