Instructions to use greatakela/deep_pavlov__qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use greatakela/deep_pavlov__qa_model 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="greatakela/deep_pavlov__qa_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("greatakela/deep_pavlov__qa_model") model = AutoModelForQuestionAnswering.from_pretrained("greatakela/deep_pavlov__qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from greatakela/deep_pavlov__qa_model: direct link, hf CLI and curl.
- Browser
- Download file 709 MB
-
https://huggingface.co/greatakela/deep_pavlov__qa_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://greatakela/deep_pavlov__qa_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/greatakela/deep_pavlov__qa_model/resolve/main/pytorch_model.bin
709 MB
- Xet hash:
- 1f00decea5660c4062c27bad1c6b11f4d491b7f8508ba286155c4f29bac631f9
- Size of remote file:
- 709 MB
- SHA256:
- 4c4d93bba3ccdeb7737a238e89729499d9b09107e5af71e9c12438ac57c4cc89
路
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