Instructions to use pankajrudra/MediBool-banglabert-Context_Aware with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pankajrudra/MediBool-banglabert-Context_Aware with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pankajrudra/MediBool-banglabert-Context_Aware")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pankajrudra/MediBool-banglabert-Context_Aware") model = AutoModelForSequenceClassification.from_pretrained("pankajrudra/MediBool-banglabert-Context_Aware", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39c96c07bbfb11f02022a402072d4afe25a2b764955854c18746681c59c869ea
- Size of remote file:
- 1.47 kB
- SHA256:
- d3329d8d19d40062c41e797812a36ccd8abbf4b35dfb14780c6cde097465da1a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.