Instructions to use Likich/cpu-open-coding-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Likich/cpu-open-coding-models with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Likich/cpu-open-coding-models", device_map="auto") - Notebooks
- Google Colab
- Kaggle
You need to agree to share your contact information to access this model
This repository is publicly accessible, but you have to accept the conditions to access its files and content.
These checkpoints were trained on a qualitative-coding corpus whose redistribution licence and participant-consent basis are not documented in the retained research artifact (see "Data provenance" below). Access is granted for non-commercial research use and reproduction of the accompanying paper only. You are responsible for confirming that your own use is lawful in your jurisdiction. Do not redistribute the weights or attempt to reconstruct the underlying source corpus.
Log in or Sign Up to review the conditions and access this model content.
Gated model You can list files but not access them
Preview of files found in this repository