Instructions to use dortucx/gpt2-nm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dortucx/gpt2-nm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dortucx/gpt2-nm")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dortucx/gpt2-nm") model = AutoModel.from_pretrained("dortucx/gpt2-nm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf8a544f3632f134adf932eff8513601d9b70b871d3310b63d18aeda53bb22c3
- Size of remote file:
- 498 MB
- SHA256:
- 31aa65f47cdbfa305997fcf6cb675a4d1834293d9a27af1ff7bb40aef914904e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.