Instructions to use intanm/mdeberta-webis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intanm/mdeberta-webis 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="intanm/mdeberta-webis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("intanm/mdeberta-webis") model = AutoModelForQuestionAnswering.from_pretrained("intanm/mdeberta-webis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spm.model from intanm/mdeberta-webis: direct link, hf CLI and curl.
- Browser
- Download file 4.31 MB
-
https://huggingface.co/intanm/mdeberta-webis/resolve/main/spm.model
- Command line
-
hf download hf://intanm/mdeberta-webis/spm.model
-
curl -L -o spm.model https://huggingface.co/intanm/mdeberta-webis/resolve/main/spm.model
4.31 MB
- Xet hash:
- 09276c12afb6b64ef0fe553eb9d092effe9fcdf0292a746be693a157b225dd4f
- Size of remote file:
- 4.31 MB
- SHA256:
- 13c8d666d62a7bc4ac8f040aab68e942c861f93303156cc28f5c7e885d86d6e3
路
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