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:
- 372f552fd13cc3a03af650544467e1cefa2a315a8ca59efc053a0b5980ddbfce
- Size of remote file:
- 5.2 kB
- SHA256:
- 6fdb5c3298615123560b46afa9fef58efee221d6cd90684f06641ef6f54e89bb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.