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:
- 158dd27725fcb26763387423693fb2ef12fc625945e95f4f8d2edb69c6ba45a6
- Size of remote file:
- 885 MB
- SHA256:
- 9565c29e966383fa04aa6e24b11bc5da1d961ca0068f77d70ec3d34561dc9c47
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.