Instructions to use nyu-mll/roberta-base-100M-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nyu-mll/roberta-base-100M-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nyu-mll/roberta-base-100M-3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nyu-mll/roberta-base-100M-3") model = AutoModelForMaskedLM.from_pretrained("nyu-mll/roberta-base-100M-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nyu-mll/roberta-base-100M-3: direct link, hf CLI and curl.
- Browser
- Download file 501 MB
-
https://huggingface.co/nyu-mll/roberta-base-100M-3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nyu-mll/roberta-base-100M-3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nyu-mll/roberta-base-100M-3/resolve/main/pytorch_model.bin
501 MB
- Xet hash:
- ab72994dff17f036663ae853db92fc6a96b11db21414eab3e4741fb8963d345a
- Size of remote file:
- 501 MB
- SHA256:
- f82b33a13bce65fca1552d4aa3087ec62c4505edabd4fd84cd0ef8181c0f262f
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