Instructions to use rohitsroch/indic-mALBERT-squad-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rohitsroch/indic-mALBERT-squad-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="rohitsroch/indic-mALBERT-squad-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("rohitsroch/indic-mALBERT-squad-v2") model = AutoModelForQuestionAnswering.from_pretrained("rohitsroch/indic-mALBERT-squad-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7294a3f7ff2c435fc51478c364eaa265fba4161ae5a0282cbd290f6c5bd5d49
- Size of remote file:
- 4.02 kB
- SHA256:
- 36a4262a2fb2dab058e3460ff2ccb224e8a0f1a7f2df4ca1cf82ff25acd53e42
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.