Instructions to use fffffly/albert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fffffly/albert_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fffffly/albert_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fffffly/albert_model") model = AutoModelForSequenceClassification.from_pretrained("fffffly/albert_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9904c95aef2a20aca7563d9d101484675f7dbe70fa6f94fba9fa9ff82600097a
- Size of remote file:
- 46.8 MB
- SHA256:
- 367c6e7baf3ccfe83a56265fb97d00622f53e5afcafa6d583c8358f120cc9752
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