Instructions to use uer/chinese_roberta_L-8_H-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uer/chinese_roberta_L-8_H-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="uer/chinese_roberta_L-8_H-256")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("uer/chinese_roberta_L-8_H-256") model = AutoModelForMaskedLM.from_pretrained("uer/chinese_roberta_L-8_H-256") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb69b58254277855bf3e2ed99ce7085e154d2191098ddf65a02c575463a96a65
- Size of remote file:
- 47.8 MB
- SHA256:
- 430ce5f230d841135b73b251864315226d9357810df58ea558a0685801dae8cb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.