Instructions to use morpheushoc/test_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use morpheushoc/test_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="morpheushoc/test_bert", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("morpheushoc/test_bert", trust_remote_code=True) model = AutoModel.from_pretrained("morpheushoc/test_bert", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2836faee53768d013b755824109dc585cea29e807a29c27ab5972e43c0c51109
- Size of remote file:
- 438 MB
- SHA256:
- 65ff02d3f69103e4491732b8afe5501eacbfef525b7143b8ec49e34f44dba1eb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.