Instructions to use SebastianKotstein/restberta-qa-value-parameter-matching with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SebastianKotstein/restberta-qa-value-parameter-matching 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="SebastianKotstein/restberta-qa-value-parameter-matching")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("SebastianKotstein/restberta-qa-value-parameter-matching") model = AutoModelForQuestionAnswering.from_pretrained("SebastianKotstein/restberta-qa-value-parameter-matching", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from SebastianKotstein/restberta-qa-value-parameter-matching: direct link, hf CLI and curl.
- Browser
- Download file 497 MB
-
https://huggingface.co/SebastianKotstein/restberta-qa-value-parameter-matching/resolve/main/tf_model.h5
- Command line
-
hf download hf://SebastianKotstein/restberta-qa-value-parameter-matching/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/SebastianKotstein/restberta-qa-value-parameter-matching/resolve/main/tf_model.h5
497 MB
- Xet hash:
- d74a12cd5f40bf44301b5a436b245e7d6c4790e11a21e551ceb74c469e29a7ed
- Size of remote file:
- 497 MB
- SHA256:
- fa040268781a12bd87da5be32a9c5e59123865721e79678a33db343e5137a608
路
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