Text Generation
PEFT
Safetensors
English
conversion-rate-optimization
cro
lora
sft
llama3.1
a-b-testing
marketing-ai
conversational
Instructions to use Keak-AI/keak-CRO-llama-3.1-8B-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Keak-AI/keak-CRO-llama-3.1-8B-instruct with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "Keak-AI/keak-CRO-llama-3.1-8B-instruct") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 733a93c79f8042f14edad6d089aa6cb15a3f3ec55e780fe630448f0bc404f901
- Size of remote file:
- 6.23 kB
- SHA256:
- 3ddb0dd8790e61e8320557818c0a80f6ee70568466c2104d2675adf2e0022adb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.