Instructions to use pstroe/roberta-base-latin-cased2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pstroe/roberta-base-latin-cased2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pstroe/roberta-base-latin-cased2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pstroe/roberta-base-latin-cased2") model = AutoModelForMaskedLM.from_pretrained("pstroe/roberta-base-latin-cased2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from pstroe/roberta-base-latin-cased2: direct link, hf CLI and curl.
- Browser
- Download file 445 MB
-
https://huggingface.co/pstroe/roberta-base-latin-cased2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://pstroe/roberta-base-latin-cased2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/pstroe/roberta-base-latin-cased2/resolve/main/pytorch_model.bin
445 MB
- Xet hash:
- 267159a14d21884ef98cfa6fcb238050b47840cc684fc3fe13707021763c1d83
- Size of remote file:
- 445 MB
- SHA256:
- 937d5fa2d9dc943cc21a34dc1ad78ce913dde6ab2cf95bbc8a784c4ef368d000
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