Instructions to use Serega6678/prototype_joint_trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Serega6678/prototype_joint_trained with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "Serega6678/prototype_joint_trained") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
acd72fd | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:83b954d34248394117f3285ae60cb26b5583f52dba1d2f1601296096333fc136
size 4856
|