Instructions to use abhi1nandy2/Europarl-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abhi1nandy2/Europarl-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="abhi1nandy2/Europarl-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("abhi1nandy2/Europarl-roberta-base") model = AutoModelForMaskedLM.from_pretrained("abhi1nandy2/Europarl-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from abhi1nandy2/Europarl-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/abhi1nandy2/Europarl-roberta-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://abhi1nandy2/Europarl-roberta-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/abhi1nandy2/Europarl-roberta-base/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 2c5e77512914e0e2b8bc9e236cbab471df255fe628b7d7ef432dfef1ac05aeb7
- Size of remote file:
- 499 MB
- SHA256:
- c77998345c310184f4983a127ef53f4eaa65867f472b4131e99b07c26c64659a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.