Instructions to use blackhole33/ExtractQuestionAnswer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blackhole33/ExtractQuestionAnswer 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="blackhole33/ExtractQuestionAnswer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("blackhole33/ExtractQuestionAnswer") model = AutoModelForQuestionAnswering.from_pretrained("blackhole33/ExtractQuestionAnswer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from blackhole33/ExtractQuestionAnswer: direct link, hf CLI and curl.
- Browser
- Download file 376 Bytes
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https://huggingface.co/blackhole33/ExtractQuestionAnswer/resolve/main/README.md
- Command line
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hf download hf://blackhole33/ExtractQuestionAnswer/README.md
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curl -L -o README.md https://huggingface.co/blackhole33/ExtractQuestionAnswer/resolve/main/README.md
376 Bytes
| license: mit | |
| # Model description | |
| **ExtractQuestionAnswer** model bu open-source modellardan olindi, | |
| asosiy maqsat dataset taxlash uchun ishlatiladi. | |
| Foydalanuvchilar bemalol kunlik tasklarni bajarish uchun ishlatsa bo'ladi, | |
| va Space workspace ham mavjud. | |
| Keyinchlik kuchli va Abstract model ishlab chiqarish uchun ishlatiladi. | |
| Dataset ko'rinishi: SQUAD kabi bo'adi. |