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:
- e07381dc67a2933fe7114edd7b94fecb0ce14a3198756a691ce0f6a8f8ee207d
- Size of remote file:
- 20.8 MB
- SHA256:
- c66570f9b0c0a41a972bd7e0c1832f28163694fd4f33009f295bd3535e8a6548
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.