Instructions to use nyu-mll/roberta-base-1B-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nyu-mll/roberta-base-1B-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nyu-mll/roberta-base-1B-3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nyu-mll/roberta-base-1B-3") model = AutoModelForMaskedLM.from_pretrained("nyu-mll/roberta-base-1B-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nyu-mll/roberta-base-1B-3: direct link, hf CLI and curl.
- Browser
- Download file 501 MB
-
https://huggingface.co/nyu-mll/roberta-base-1B-3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nyu-mll/roberta-base-1B-3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nyu-mll/roberta-base-1B-3/resolve/main/pytorch_model.bin
501 MB
- Xet hash:
- 2fd8623bcd2cf5d9e25331839dfc6d36284ce263f6f06b9fa576b16480754f99
- Size of remote file:
- 501 MB
- SHA256:
- 0eafc233f09e1fbe40117653dc27bcc45fad4b7cef7c6ae26faac8ef80138107
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