Instructions to use leomaurodesenv/bert-basketball-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leomaurodesenv/bert-basketball-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="leomaurodesenv/bert-basketball-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("leomaurodesenv/bert-basketball-qa") model = AutoModelForQuestionAnswering.from_pretrained("leomaurodesenv/bert-basketball-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-3500/optimizer.pt from leomaurodesenv/bert-basketball-qa: direct link, hf CLI and curl.
- Browser
- Download file 871 MB
-
https://huggingface.co/leomaurodesenv/bert-basketball-qa/resolve/main/checkpoint-3500/optimizer.pt
- Command line
-
hf download hf://leomaurodesenv/bert-basketball-qa/checkpoint-3500/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/leomaurodesenv/bert-basketball-qa/resolve/main/checkpoint-3500/optimizer.pt
871 MB
- Xet hash:
- 01dee4690f249b81ea723feda0d670c6564cde6fdd907fcfe17f25ad33cdbb94
- Size of remote file:
- 871 MB
- SHA256:
- 107e29da3599278582a5c9b573ad32f20f987f4fd5b05314e41920edb9623b9d
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.