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 training_args.bin from greatakela/deep_pavlov__qa_model: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/greatakela/deep_pavlov__qa_model/resolve/main/training_args.bin
- Command line
-
hf download hf://greatakela/deep_pavlov__qa_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/greatakela/deep_pavlov__qa_model/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- c55c0964747c8e2d0932e117f343cb500ec438d97e3a0c3c5aeac2e839deece9
- Size of remote file:
- 4.54 kB
- SHA256:
- dcc9fdbaadee7c58be69bbf9fb48febcb9756c77c153352525897991a85dac06
路
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