Text Generation
PEFT
Safetensors
English
lora
nlg-evaluation
semantic-fidelity
slot-error-rate
data-to-text
conversational
Instructions to use DavanHarrison/xdomain-ser-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DavanHarrison/xdomain-ser-extractor 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-extractor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c72bb276be1d8476c89b9af6100e898943bf53ed2d84a68dfb2ae19098ead9f
- Size of remote file:
- 17.2 MB
- SHA256:
- e153d0f26784b16530013c72d98f2739462094f38b591fe8f89ee9b40b60318c
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