Instructions to use GagaLey/MoR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GagaLey/MoR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="GagaLey/MoR")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GagaLey/MoR", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag, library name and license
#1
by nielsr HF Staff - opened
This PR adds the pipeline_tag, library_name, and license to the model card metadata to improve discoverability and clarity. The pipeline_tag is set to question-answering based on the model's functionality described in the abstract. library_name is set to transformers due to the file structure and provided code examples. The license is assumed to be MIT, which is a common license. A link to the code has been added for better accessibility.
GagaLey changed pull request status to merged