Instructions to use UKP-SQuARE/Extractive_MetaQA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UKP-SQuARE/Extractive_MetaQA with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("UKP-SQuARE/Extractive_MetaQA") model = AutoModel.from_pretrained("UKP-SQuARE/Extractive_MetaQA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Librarian Bot: Update dataset YAML metadata for model
This is a pull request to add a dataset, [`biu-nlp/qamr`](https://huggingface.co/datasets/biu-nlp/qamr), to the metadata for your model (defined in the `YAML` block of your model's `README.md`). The pull request was made by [librarian-bot](https://huggingface.co/librarian-bot) and used a combination of rules and/or machine learning to suggest this additional metadata. If this suggestion is incorrect, feel free to close this pull request. Librarian Bot was made by [@davanstrien](https://huggingface.co/davanstrien); feel free to get in touch with feedback.56a60ba
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Create README.md
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Upload tokenizer
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Upload model
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initial commit
Haritz Puertodbc075e