Instructions to use Kyrmasch/xml-roberta-model-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kyrmasch/xml-roberta-model-qa 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="Kyrmasch/xml-roberta-model-qa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Kyrmasch/xml-roberta-model-qa") model = AutoModelForQuestionAnswering.from_pretrained("Kyrmasch/xml-roberta-model-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Kyrmasch/xml-roberta-model-qa: direct link, hf CLI and curl.
- Browser
- Download file 2.22 GB
-
https://huggingface.co/Kyrmasch/xml-roberta-model-qa/resolve/refs%2Fpr%2F2/optimizer.pt
- Command line
-
hf download hf://Kyrmasch/xml-roberta-model-qa@refs/pr/2/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Kyrmasch/xml-roberta-model-qa/resolve/refs%2Fpr%2F2/optimizer.pt
2.22 GB
- Xet hash:
- bb66f6de0f07ce379102d78874b58bf452fb8a569f81df6d54bf50917877bfea
- Size of remote file:
- 2.22 GB
- SHA256:
- 415cf20de7fc969bd9767f8c02e4f1b23d8585605f8634e4fbabb09dfb068390
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