Text Generation
PEFT
Safetensors
English
lora
qwen2
echo-omega-prime
software-engineering
devops
architecture
ci-cd
cloud
conversational
Instructions to use Bmcbob76/echo-software-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Bmcbob76/echo-software-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-7B-Instruct") model = PeftModel.from_pretrained(base_model, "Bmcbob76/echo-software-adapter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 269da9e48f5b5c97df6f5b872b4897db13aa9559f94cea68a45553aee52e85fe
- Size of remote file:
- 5.5 kB
- SHA256:
- 0f7aa88d1abe19bda971df8036d1beba09e8c86cd2588aac7f0bf77a05424bbc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.