Instructions to use sshh12/Mistral-7B-LoRA-Multi-VisionCLIPPool-LLAVA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sshh12/Mistral-7B-LoRA-Multi-VisionCLIPPool-LLAVA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") model = PeftModel.from_pretrained(base_model, "sshh12/Mistral-7B-LoRA-Multi-VisionCLIPPool-LLAVA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c9d15e8d1ebf11f998451a4eafffd81200c83590988f2ba44d2d700f3e07fc0
- Size of remote file:
- 420 MB
- SHA256:
- b114627deef3f20cb0fd831eb9b1316f59038e1cbb1050f1e3b0afaf10a99935
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