Instructions to use Jennny/eng_rm_1e5_700 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jennny/eng_rm_1e5_700 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jennny/eng_rm_1e5_700")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jennny/eng_rm_1e5_700") model = AutoModelForSequenceClassification.from_pretrained("Jennny/eng_rm_1e5_700") - Notebooks
- Google Colab
- Kaggle
Add model card for Engagement Process Reward Model
#1
by nielsr HF Staff - opened
This PR adds a model card for the Engagement Process Reward Model (PRM) introduced in the paper "Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards".
The model card includes:
- Metadata for the
transformerslibrary andtext-classificationpipeline tag. - Information about the model's role in the MAHALO framework.
- Links to the paper and the official GitHub repository.
- The BibTeX citation for the work.
Jennny changed pull request status to merged