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:
- 41038a82a288c5f8b6f71f784f6597a7b0f0df3917e7e5ea65d2f928374885d8
- Size of remote file:
- 6.83 MB
- SHA256:
- 550ef1e9953dbdf974619f3ca71e93b18fcbbcfcddbdc0469900e33d35828701
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