Instructions to use sshleifer/tiny-distilroberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sshleifer/tiny-distilroberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sshleifer/tiny-distilroberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sshleifer/tiny-distilroberta-base") model = AutoModelForMaskedLM.from_pretrained("sshleifer/tiny-distilroberta-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 460b2bc2b54d4c799b6a69b533c301a9d140d4a9a8de0a12fd5a194d24e1faf9
- Size of remote file:
- 1.09 MB
- SHA256:
- 7f99567055741013507be3953d03cb0332ef7338f083ee8bfceb5ecb267ff03b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.