Instructions to use dani0f/DomainAdaptM2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dani0f/DomainAdaptM2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dani0f/DomainAdaptM2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dani0f/DomainAdaptM2") model = AutoModel.from_pretrained("dani0f/DomainAdaptM2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 704a8aadf41efae09124fc01f4531b361789ce420afc521ffdcd97850f26ba4a
- Size of remote file:
- 438 MB
- SHA256:
- b4e45ae5456d1c8e8229c6b0113cdb32f444ef1d6cafe932d8aebe20ca1af8f2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.