Instructions to use Matheusmatos2916/my_awesome_qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Matheusmatos2916/my_awesome_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="Matheusmatos2916/my_awesome_qa_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Matheusmatos2916/my_awesome_qa_model") model = AutoModelForQuestionAnswering.from_pretrained("Matheusmatos2916/my_awesome_qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Matheusmatos2916/my_awesome_qa_model: direct link, hf CLI and curl.
- Browser
- Download file 4.47 kB
-
https://huggingface.co/Matheusmatos2916/my_awesome_qa_model/resolve/main/training_args.bin
- Command line
-
hf download hf://Matheusmatos2916/my_awesome_qa_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Matheusmatos2916/my_awesome_qa_model/resolve/main/training_args.bin
4.47 kB
- Xet hash:
- bc447d8f5d863bf903917e4155ca45af19b4724cb5f5866f982a68e17e1cca9a
- Size of remote file:
- 4.47 kB
- SHA256:
- 84aa0e2a983035197ada588c2a85bfc5a01a3bfc7b21f04d62dc1ebbd34cc5fe
路
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