Instructions to use AliBagherz/result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AliBagherz/result with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="AliBagherz/result")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("AliBagherz/result") model = AutoModelForQuestionAnswering.from_pretrained("AliBagherz/result", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58b1d0c2de9eac874ba419ddea69e86ddd92515530858648eb08e5609f79913d
- Size of remote file:
- 4.03 kB
- SHA256:
- af024fa6e26303a22c5b367aec3e7dc9b7f2da1572a4b867a5a8b9214ba176eb
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