Instructions to use harish/PT-mbert-train-from-test-and-dev-FalseTrue-0_0_BEST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harish/PT-mbert-train-from-test-and-dev-FalseTrue-0_0_BEST with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harish/PT-mbert-train-from-test-and-dev-FalseTrue-0_0_BEST")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harish/PT-mbert-train-from-test-and-dev-FalseTrue-0_0_BEST") model = AutoModelForSequenceClassification.from_pretrained("harish/PT-mbert-train-from-test-and-dev-FalseTrue-0_0_BEST", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b400844692e77561b435b72a100ea5364b21fbfb41e5b4c55da6576c544272d
- Size of remote file:
- 711 MB
- SHA256:
- 0a81454052297797ba1177cc38760542984e4f0fb548a92201618c659ef80c63
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