Text Generation
PEFT
Safetensors
English
lora
nlg-evaluation
reranking
over-generate-and-rank
conversational
Instructions to use DavanHarrison/xdomain-ser-ranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DavanHarrison/xdomain-ser-ranker with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct") model = PeftModel.from_pretrained(base_model, "DavanHarrison/xdomain-ser-ranker") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46fd8900259bf48e36fb9ade809f6d6f2c8641e831b48dc7f0a50f3c5aa9566f
- Size of remote file:
- 17.2 MB
- SHA256:
- a5e37933096363473c7058aae28672ae6a20e37ffc8d931ab5dcbe3aae9e3624
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