Instructions to use messawey/qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use messawey/qa_model 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="messawey/qa_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("messawey/qa_model") model = AutoModelForQuestionAnswering.from_pretrained("messawey/qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from messawey/qa_model: direct link, hf CLI and curl.
- Browser
- Download file 266 MB
-
https://huggingface.co/messawey/qa_model/resolve/main/tf_model.h5
- Command line
-
hf download hf://messawey/qa_model/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/messawey/qa_model/resolve/main/tf_model.h5
266 MB
- Xet hash:
- 39b261b029e10723cc7ffde82788e34f7f1e76ecdf3d7f2a469dc010cb335163
- Size of remote file:
- 266 MB
- SHA256:
- 2e9c6642688e18fff92b47880fb7bc5eedc773e951a299f15670d10122d88f1d
路
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