Instructions to use twielema/trained20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use twielema/trained20 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="twielema/trained20")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("twielema/trained20") model = AutoModelForQuestionAnswering.from_pretrained("twielema/trained20", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a7dddd2dd1e99f222f8a318aeb6f32b5d06f0136a46a36bc1afe2b51ccb2153
- Size of remote file:
- 669 kB
- SHA256:
- 2188b7f5b546e9fa273f95b79584f569dd9bff5ccf584f36c712a67ac42655ff
路
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