Instructions to use trohith89/cod-bert-codmobile with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trohith89/cod-bert-codmobile with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="trohith89/cod-bert-codmobile")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("trohith89/cod-bert-codmobile") model = AutoModelForSequenceClassification.from_pretrained("trohith89/cod-bert-codmobile") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c76cb24e6cc16c0549d85b86dcca9c8ca223db783e4e74521348c547691c0266
- Size of remote file:
- 438 MB
- SHA256:
- b94e8e2f7a9db859e2f06037fa00aa02c264d6ee88e6d3d10ad462013809bb04
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.