Instructions to use ALBADDAWI/ft-mistralai-Mistral-7B-Instruct-v0.2-qlora-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ALBADDAWI/ft-mistralai-Mistral-7B-Instruct-v0.2-qlora-v2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") model = PeftModel.from_pretrained(base_model, "ALBADDAWI/ft-mistralai-Mistral-7B-Instruct-v0.2-qlora-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0cd60276b9954a88afc776edef56eef9404e0cd6d9d9d7a340f7095f1fea752d
- Size of remote file:
- 1.22 GB
- SHA256:
- 1da3901ceb2630ff5a73149a1964b15a72ad5af7943e33dadb54d370057edf95
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