Instructions to use Sybghat/Testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sybghat/Testing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Sybghat/Testing")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Sybghat/Testing") model = AutoModelForQuestionAnswering.from_pretrained("Sybghat/Testing") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- baf119e528f9dac8747a2bd286fbb3eb7ef63a941c48498106bdbb600a43e0ac
- Size of remote file:
- 265 MB
- SHA256:
- 55fe5b06c74ad9ce89e62bb0fb8103b2270fe76beda0667f0913b5a8ecbd105e
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.