Instructions to use iamew/trained_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iamew/trained_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="iamew/trained_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("iamew/trained_model") model = AutoModelForQuestionAnswering.from_pretrained("iamew/trained_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f7d271d753b062dee8e5a1f9443e1cce9ec2eef36089b2c033a2e50ad1f2fab
- Size of remote file:
- 54 MB
- SHA256:
- 92828df4e81d51661923081d3079d7fafacb37590acd24039bf9d642bb17d587
路
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