Instructions to use MLMvsCLM/1b-mlm30-42k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MLMvsCLM/1b-mlm30-42k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MLMvsCLM/1b-mlm30-42k", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MLMvsCLM/1b-mlm30-42k", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add link to GitHub repository and refine usage example
#1
by nielsr HF Staff - opened
This PR improves the model card by:
- Adding a direct link to the associated GitHub repository (
https://github.com/Nicolas-BZRD/EuroBERT), making it easier for users to find the underlying code. - Refining the usage example by replacing the placeholder model ID (
<YOUR_MODEL_ID_HERE>) with a concrete, representative model ID (AhmedAliHassan/MLMvsCLM-Biphasic-210M). This provides users with a ready-to-use example for feature extraction.