Instructions to use jschew39/GenerAd-AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use jschew39/GenerAd-AI with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("jschew39/GenerAd-AI", set_active=True) - Notebooks
- Google Colab
- Kaggle
metadata
library_name: adapter-transformers
license: bigscience-openrail-m
datasets:
- generativeaidemo/generadai-sample
pipeline_tag: text-generation
Training procedure
The following bitsandbytes quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: True
- load_in_4bit: False
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
Framework versions
- PEFT 0.6.0.dev0