Instructions to use KashiwaByte/Read_Comprehension_MiniCPM2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use KashiwaByte/Read_Comprehension_MiniCPM2B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("./OpenBMB/MiniCPM-2B-sft-fp32") model = PeftModel.from_pretrained(base_model, "KashiwaByte/Read_Comprehension_MiniCPM2B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aac6507d4720aee0ecdd1b82997cb0348e6ae634da787b793e1b9d556c5b479a
- Size of remote file:
- 5.92 MB
- SHA256:
- e88cb12fda94b0b46d5d8c8b9c7878d7c928b486d549c7207ed16557fc01a051
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.