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 tokenizer.json from StaAhmed/Model_QA: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/StaAhmed/Model_QA/resolve/main/tokenizer.json
- Command line
-
hf download hf://StaAhmed/Model_QA/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/StaAhmed/Model_QA/resolve/main/tokenizer.json
712 kB
- Xet hash:
- 9b551add00a0ef6400579332840d7dbc2af83b1d86cca64acd085a7353778a76
- Size of remote file:
- 712 kB
- SHA256:
- 64c5c7149ef8d127e48b4f8c3befa915ca04cf1a34f91f1e4cdde17628ef7cd7
路
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