Question Answering
Adapters
English
falcon
QLoRA
Adapters
llms
Transformers
Fine-Tuning
PEFT
SFTTrainer
Open-Source
LoRA
Attention
code
Falcon-7b
custom_code
Instructions to use avnishkr/falcon-QAMaster with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use avnishkr/falcon-QAMaster with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("fill-in-model-name") model.load_adapter("avnishkr/falcon-QAMaster", set_active=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bdbd8d0cc890fc2dfe9441d0f7a2eea645827465bca9833b2bbb2b6470cceb72
- Size of remote file:
- 1.04 GB
- SHA256:
- 65e898b7afc60bf764f1a27f93aeca7043428e519b722bfc4df5acede927ecc5
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.