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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1dbd7b2dddcc022dc882ad662ea30f7a9be87e43d226ac2241c50c5f21569023
- Size of remote file:
- 5.43 kB
- SHA256:
- 5b2816e3d34d1d3d39668e726e88c6e880a8cb8be82654e2ac4138f84e3e64fa
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