Instructions to use pln-udelar/rouberta-base-uy22-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pln-udelar/rouberta-base-uy22-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pln-udelar/rouberta-base-uy22-cased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pln-udelar/rouberta-base-uy22-cased") model = AutoModelForMaskedLM.from_pretrained("pln-udelar/rouberta-base-uy22-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from pln-udelar/rouberta-base-uy22-cased: direct link, hf CLI and curl.
- Browser
- Download file 877 MB
-
https://huggingface.co/pln-udelar/rouberta-base-uy22-cased/resolve/main/optimizer.pt
- Command line
-
hf download hf://pln-udelar/rouberta-base-uy22-cased/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/pln-udelar/rouberta-base-uy22-cased/resolve/main/optimizer.pt
877 MB
- Xet hash:
- 0f6f175b5861ae57286ac713ec1d097a8eee6dd844f514bb733a12dc0ac42959
- Size of remote file:
- 877 MB
- SHA256:
- 2c344206802676a4c1c6c7ed3dc503a63517a79aaf7a9a4ab8690235fa7cb732
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