Instructions to use AyaKhaled/phi_vision_checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AyaKhaled/phi_vision_checkpoints with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("llava-hf/llava-1.5-7b-hf") model = PeftModel.from_pretrained(base_model, "AyaKhaled/phi_vision_checkpoints") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
README.md
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library_name: peft
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# phi_vision_checkpoints
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This model is a fine-tuned version of [
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## Model description
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library_name: peft
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license: llama2
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base_model: llava-hf/llava-1.5-7b-hf
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tags:
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- generated_from_trainer
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model-index:
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# phi_vision_checkpoints
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This model is a fine-tuned version of [llava-hf/llava-1.5-7b-hf](https://huggingface.co/llava-hf/llava-1.5-7b-hf) on an unknown dataset.
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## Model description
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