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 pytorch_model.bin from Sahajtomar/GBERTQnA: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/Sahajtomar/GBERTQnA/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Sahajtomar/GBERTQnA/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sahajtomar/GBERTQnA/resolve/main/pytorch_model.bin
1.34 GB
- Xet hash:
- af7f2380ec75e46d9d5b0f5d1f7da5cdf3cf56e6a4a8890b50d111de8297e210
- Size of remote file:
- 1.34 GB
- SHA256:
- 802b495c87c8a1ae6d6297da37cb6533621a71285fc502ff15faae799ae4a028
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