Instructions to use HanningZhang/Llama3.1-RAG-Reward with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HanningZhang/Llama3.1-RAG-Reward with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HanningZhang/Llama3.1-RAG-Reward")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HanningZhang/Llama3.1-RAG-Reward") model = AutoModelForSequenceClassification.from_pretrained("HanningZhang/Llama3.1-RAG-Reward", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload LlamaForCausalLM
Browse files
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