Fill-Mask
Transformers
PyTorch
Safetensors
Icelandic
English
multilingual
xlm-roberta
icelandic
xlmr
Instructions to use vesteinn/XLMR-ENIS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vesteinn/XLMR-ENIS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="vesteinn/XLMR-ENIS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("vesteinn/XLMR-ENIS") model = AutoModelForMaskedLM.from_pretrained("vesteinn/XLMR-ENIS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from vesteinn/XLMR-ENIS: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/vesteinn/XLMR-ENIS/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://vesteinn/XLMR-ENIS/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/vesteinn/XLMR-ENIS/resolve/main/pytorch_model.bin
498 MB
- Xet hash:
- 54193dba498e371810899b4271530e863396adf2dee4886c46da31673fee4f43
- Size of remote file:
- 498 MB
- SHA256:
- 8a578bb4b5697043cdacbba7fbc1605c8d3c7a03e73f857ebba4e3fcc76ba5e4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.