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 2.16 GB
-
https://huggingface.co/Kyrmasch/xml-roberta-model-qa/resolve/refs%2Fpr%2F4/optimizer.pt
- Command line
-
hf download hf://Kyrmasch/xml-roberta-model-qa@refs/pr/4/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Kyrmasch/xml-roberta-model-qa/resolve/refs%2Fpr%2F4/optimizer.pt
2.16 GB
- Xet hash:
- 5463136c9e5a5b0d87854fe9f8252a1160478d78a1c20b74f1062577597e8476
- Size of remote file:
- 2.16 GB
- SHA256:
- cb4ba9d920882db665a7f8ed561c2e0164bf7175d907c1270c05e7520cdcb1d0
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