Instructions to use olm/olm-roberta-base-latest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use olm/olm-roberta-base-latest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="olm/olm-roberta-base-latest")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("olm/olm-roberta-base-latest") model = AutoModelForMaskedLM.from_pretrained("olm/olm-roberta-base-latest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from olm/olm-roberta-base-latest: direct link, hf CLI and curl.
- Browser
- Download file 2.12 MB
-
https://huggingface.co/olm/olm-roberta-base-latest/resolve/main/tokenizer.json
- Command line
-
hf download hf://olm/olm-roberta-base-latest/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/olm/olm-roberta-base-latest/resolve/main/tokenizer.json
2.12 MB
File too large to display, you can check the raw version instead.