Text Classification
Transformers
Safetensors
llama
Generated from Trainer
reward-model
mahalo
text-embeddings-inference
Instructions to use Jennny/llama3_8b_helpful_rm_full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jennny/llama3_8b_helpful_rm_full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jennny/llama3_8b_helpful_rm_full")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jennny/llama3_8b_helpful_rm_full") model = AutoModelForSequenceClassification.from_pretrained("Jennny/llama3_8b_helpful_rm_full") - Notebooks
- Google Colab
- Kaggle
Link model to paper and repository, add pipeline tag
#1
by nielsr HF Staff - opened
Hi! I'm Niels, part of the community science team at Hugging Face.
This PR improves the model card by:
- Linking it to the associated paper: Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards.
- Adding a link to the official GitHub repository.
- Specifying the
text-classificationpipeline tag to ensure the model is correctly categorized on the Hub (as it is a sequence classification/reward model). - Providing context about the model's role as a Helpfulness Reward Model within the MAHALO framework.
Jennny changed pull request status to merged