Text Generation
PEFT
Safetensors
English
llama
adaption-labs
autoscientist
marketing
campaign-optimization
budget-allocation
roas
lora
hackathon
conversational
Instructions to use narendarcodes/adaption-multichannel-campaign-optimizer-70b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use narendarcodes/adaption-multichannel-campaign-optimizer-70b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("togethercomputer/Meta-Llama-3.3-70B-Instruct-Reference") model = PeftModel.from_pretrained(base_model, "narendarcodes/adaption-multichannel-campaign-optimizer-70b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da070f8626ee36c29d81d14f7a18b0a943ba6477aaa86b433d0f865f98bf8392
- Size of remote file:
- 17.2 MB
- SHA256:
- 6b9e4e7fb171f92fd137b777cc2714bf87d11576700a1dcd7a399e7bbe39537b
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