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%2F5/optimizer.pt
- Command line
-
hf download hf://Kyrmasch/xml-roberta-model-qa@refs/pr/5/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Kyrmasch/xml-roberta-model-qa/resolve/refs%2Fpr%2F5/optimizer.pt
2.22 GB
- Xet hash:
- a3e1a20515ad47021634ccc0b7530ce18a8158dee8c012cc32f5ce50ffcaf37b
- Size of remote file:
- 2.22 GB
- SHA256:
- b7f616dd892d65e0d0839627fbdb98aa327b78ef38f72e08bffe2ebe0a7e0ef2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.