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:
- 154c7a80066645c3a5f8006847269f0e353f8331b26c0e5153bda7ff8007f7f1
- Size of remote file:
- 131 MB
- SHA256:
- e5522653c1df356658938e9694dd5e161a02c4b62b1be9bae2d4d458e7045ea5
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.