Instructions to use MaoXun/llava-lora-vicuna-7b-v1.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MaoXun/llava-lora-vicuna-7b-v1.3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lmsys/vicuna-7b-v1.3") model = PeftModel.from_pretrained(base_model, "MaoXun/llava-lora-vicuna-7b-v1.3") - Notebooks
- Google Colab
- Kaggle
Specify right model card metadata (#2)
Browse files- Specify right model card metadata (878970af723c0ba65bb84d174beb3d93dd46c3c3)
Co-authored-by: Omar Sanseviero <osanseviero@users.noreply.huggingface.co>
README.md
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library_name: peft
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base_model: lmsys/vicuna-7b-v1.3
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## Training procedure
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library_name: peft
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tags:
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- llava
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base_model: lmsys/vicuna-7b-v1.3
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pipeline_tag: image-text-to-text
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## Training procedure
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