Instructions to use Aybars/ModelOnWhole with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aybars/ModelOnWhole with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Aybars/ModelOnWhole", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Aybars/ModelOnWhole") model = AutoModelForQuestionAnswering.from_pretrained("Aybars/ModelOnWhole", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
7116e46 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:79c7b6ecf07e8ba89c5176ebc257b50a7060d3db551001610dca38565bfb3977
size 735108529
|