Instructions to use codegenstudio/codegen-350M-nosql2doc-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use codegenstudio/codegen-350M-nosql2doc-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/kaggle/working/models/base/Salesforce__codegen-350M-multi") model = PeftModel.from_pretrained(base_model, "codegenstudio/codegen-350M-nosql2doc-lora") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4438b2bc1ccf0ff7d9819e2690d9c1e740f0e3e365038517a29cba784a088d5b
- Size of remote file:
- 5.84 kB
- SHA256:
- a46feeb2eab16954d3fefe8cda13490c466c544ca6063b8067a5806d5b663b51
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.