Instructions to use MLMvsCLM/210m-clm-42k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MLMvsCLM/210m-clm-42k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MLMvsCLM/210m-clm-42k", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MLMvsCLM/210m-clm-42k", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add link to code repository
#1
by nielsr HF Staff - opened
This PR improves the model card by adding a direct link to the GitHub repository associated with the paper "Should We Still Pretrain Encoders with Masked Language Modeling?" (https://github.com/nicolas-bzrd/mlmvscclm). This enhances the discoverability of the code artifacts for users.