Instructions to use prithivMLmods/MBERT-Context-Specifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/MBERT-Context-Specifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prithivMLmods/MBERT-Context-Specifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("prithivMLmods/MBERT-Context-Specifier") model = AutoModelForSequenceClassification.from_pretrained("prithivMLmods/MBERT-Context-Specifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9618975c22dabb7353fac8927b6c7c187bf7dd401fa8ac490fbfad5b4f5c87b7
- Size of remote file:
- 599 MB
- SHA256:
- ec3c9c14d079364b640b64a52aa11307e5ea429798f5e3975bedb0a59b1af8ff
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