Text Generation
PEFT
Safetensors
English
gherkin
bdd
test-automation
cucumber
lora
deepseek
conversational
Instructions to use Ghaythfd/gherkin-deepseek-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ghaythfd/gherkin-deepseek-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-instruct") model = PeftModel.from_pretrained(base_model, "Ghaythfd/gherkin-deepseek-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8778136037be2155be36c95f9493190329ec16c2f24697b981c3fa3d11de33a8
- Size of remote file:
- 160 MB
- SHA256:
- 71388552105c7aebe06e710a32e91ba51756e385789775e5c26f56b7867945f0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.