Instructions to use Sahajtomar/GBERTQnA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sahajtomar/GBERTQnA with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Sahajtomar/GBERTQnA")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Sahajtomar/GBERTQnA") model = AutoModelForQuestionAnswering.from_pretrained("Sahajtomar/GBERTQnA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Sahajtomar/GBERTQnA: direct link, hf CLI and curl.
- Browser
- Download file 1.65 kB
-
https://huggingface.co/Sahajtomar/GBERTQnA/resolve/main/training_args.bin
- Command line
-
hf download hf://Sahajtomar/GBERTQnA/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Sahajtomar/GBERTQnA/resolve/main/training_args.bin
1.65 kB
- Xet hash:
- f02f60f7f389d2024cb080ee3c9a28849383c459722dee4d7f3df77e004d21a2
- Size of remote file:
- 1.65 kB
- SHA256:
- 7c12a4793601e4a87e0c06bdc349e73a7d4b486660982dda102e769115cce98c
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