# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("flax-community/robit-roberta-base-it")
model = AutoModelForMaskedLM.from_pretrained("flax-community/robit-roberta-base-it")Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
RobIt
RobIt is a RoBERTa-base model for Italian. It has been trained from scratch on the Italian portion of the OSCAR dataset using Flax, including training scripts.
This is part of the Flax/Jax Community Week, organised by HuggingFace and TPU usage sponsored by Google.
Team members
- Prateek Agrawal (prateekagrawal)
- Tanay Mehta (yotanay)
- Shreya Gupta (Sheyz-max)
- Ruchi Bhatia (ruchi798)
Dataset :
- config : unshuffled_deduplicated_it
- Size of downloaded dataset files: 26637.62 MB
- Size of the generated dataset: 70661.48 MB
- Total amount of disk used: 97299.10 MB
Useful links
- Downloads last month
- 6
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="flax-community/robit-roberta-base-it")