Instructions to use Logeswaransr/sample_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Logeswaransr/sample_finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Logeswaransr/sample_finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Logeswaransr/sample_finetuned") model = AutoModelForQuestionAnswering.from_pretrained("Logeswaransr/sample_finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1fcefa99a6b85e7ccf31ea3e25e29d85de9fdef971376eb28fa4b0ad261c5068
- Size of remote file:
- 265 MB
- SHA256:
- acf68c150cb308c4d9dca16dfde6816f06e99fdc67e4016fd02f0378e2999aed
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.