Instructions to use NCSOFT/Llama-3-OffsetBias-RM-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NCSOFT/Llama-3-OffsetBias-RM-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NCSOFT/Llama-3-OffsetBias-RM-8B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NCSOFT/Llama-3-OffsetBias-RM-8B") model = AutoModelForSequenceClassification.from_pretrained("NCSOFT/Llama-3-OffsetBias-RM-8B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Difference in code example between here and github
#1
by fabriceyhc - opened
Which code example is recommended?
Your github repo code looks much different. The one here uses a "sentiment-analysis" pipeline, which is unexpected / unintuitive.
For the reward model, this code(huggingface) is recommended since github repo currently supports the generative model only.