Instructions to use hung200504/distil-bert-6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/distil-bert-6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hung200504/distil-bert-6")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/distil-bert-6") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/distil-bert-6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 106759ca2e961e4b2d6a65244d324e3afbb3dcc6dbf8d85eedca95737fed08e9
- Size of remote file:
- 4.09 kB
- SHA256:
- 1c06042780c027ce9a970b34940680c03828d57a461cedb41f8218bbfa72f0f7
路
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