Instructions to use Amalq/stress-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amalq/stress-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Amalq/stress-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Amalq/stress-roberta-base") model = AutoModelForMaskedLM.from_pretrained("Amalq/stress-roberta-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a9df01277aef54e8578eee4c3e0fea92be7c26e4189f655d7ce1fd5e9aa8ea4
- Size of remote file:
- 499 MB
- SHA256:
- 73c60864bacd755cb9345b70bb7b86bc6f142fdf50bbf39592fc52a7a59b2467
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.