# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("ClassCat/roberta-base-french")
model = AutoModelForMaskedLM.from_pretrained("ClassCat/roberta-base-french")Quick Links
RoBERTa French base model (Uncased)
Prerequisites
transformers==4.19.2
Model architecture
This model uses RoBERTa base setttings except vocabulary size.
Tokenizer
Using BPE tokenizer with vocabulary size 50,000.
Training Data
- wiki40b/fr (French Wikipedia)
- Subset of CC-100/fr : Monolingual Datasets from Web Crawl Data
Usage
from transformers import pipeline
unmasker = pipeline('fill-mask', model='ClassCat/roberta-base-french')
unmasker("Je vais à la <mask>.")
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ClassCat/roberta-base-french")