Instructions to use MarPla/BertMethodsComp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarPla/BertMethodsComp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MarPla/BertMethodsComp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MarPla/BertMethodsComp") model = AutoModelForSequenceClassification.from_pretrained("MarPla/BertMethodsComp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- afa8ba514c345e56ab0c7e4e9705c54f56bff3b1d6594caf3f2c7637f81e8b59
- Size of remote file:
- 5.11 kB
- SHA256:
- 2941848c6c868308794a1f87fa2ba02555f8329808d38564f6d99714b6ea6f54
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