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:
- 498bfe3d41f5f6106001ac169d24fd79ae59923a6ff7dfef856f0ed65fccfddb
- Size of remote file:
- 609 kB
- SHA256:
- 44ae739ff9dd7f45b29f3f4e6909658aeae152499be687af1eae9266a29e9e22
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.