Instructions to use Ifenna/dbert-3epoch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ifenna/dbert-3epoch with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Ifenna/dbert-3epoch")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Ifenna/dbert-3epoch") model = AutoModelForQuestionAnswering.from_pretrained("Ifenna/dbert-3epoch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Ifenna/dbert-3epoch: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/Ifenna/dbert-3epoch/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Ifenna/dbert-3epoch/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Ifenna/dbert-3epoch/resolve/main/pytorch_model.bin
265 MB
- Xet hash:
- 8ac20e47335495acac47e38ddb2bb91b14b5b3cca80160bd3c017d774974d998
- Size of remote file:
- 265 MB
- SHA256:
- a63adf154254d5e69ff9d06494e1c1a67b23d5c70be6c9a91ee3aeed1459ab37
路
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