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:
- a8e35e643962da873e774ec0799f9a692a878c534ca7efe572a70e09c13d133f
- Size of remote file:
- 261 MB
- SHA256:
- f34caf3e8da2d236267d5b3b45eba792b2994781df7d8a75040514f197ae649c
路
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