Instructions to use StaAhmed/Model_QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StaAhmed/Model_QA 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="StaAhmed/Model_QA")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("StaAhmed/Model_QA") model = AutoModelForQuestionAnswering.from_pretrained("StaAhmed/Model_QA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spm.model from StaAhmed/Model_QA: direct link, hf CLI and curl.
- Browser
- Download file 4.31 MB
-
https://huggingface.co/StaAhmed/Model_QA/resolve/main/spm.model
- Command line
-
hf download hf://StaAhmed/Model_QA/spm.model
-
curl -L -o spm.model https://huggingface.co/StaAhmed/Model_QA/resolve/main/spm.model
4.31 MB
- Xet hash:
- c4b914ec5ab295fbee3b0e0fe62f22febb3c09d34dd3778745e0de034a76df33
- Size of remote file:
- 4.31 MB
- SHA256:
- 13c8d666d62a7bc4ac8f040aab68e942c861f93303156cc28f5c7e885d86d6e3
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.