Instructions to use dd101bb/latentRM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dd101bb/latentRM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dd101bb/latentRM")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dd101bb/latentRM") model = AutoModelForTokenClassification.from_pretrained("dd101bb/latentRM") - Notebooks
- Google Colab
- Kaggle
Update pipeline tag and add license
#1
by nielsr HF Staff - opened
This PR updates the model card to:
- Change the
pipeline_tagfromtoken-classificationtofeature-extractionto better reflect the model's function as a learned scorer for latent reasoning. - Add the
licensetag, explicitly stating it as Apache-2.0.
dd101bb changed pull request status to merged