Instructions to use sfairXC/FsfairX-LLaMA3-RM-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sfairXC/FsfairX-LLaMA3-RM-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sfairXC/FsfairX-LLaMA3-RM-v0.1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sfairXC/FsfairX-LLaMA3-RM-v0.1") model = AutoModelForSequenceClassification.from_pretrained("sfairXC/FsfairX-LLaMA3-RM-v0.1") - Notebooks
- Google Colab
- Kaggle
Very nice model
#3
by sparsh35 - opened