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:
- ced5ed81c510e0f71a52c7d6bc2cbc4be08fc2aa7dd00a934b5dec2b58a56cd4
- Size of remote file:
- 438 MB
- SHA256:
- 3de643fa28617d40986b644f8144a182ebc3cb9e29d26d99547e8a7ec8b21c8f
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