Instructions to use KalbeDigitalLab/alpara-7b-peft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use KalbeDigitalLab/alpara-7b-peft with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("yahma/llama-7b-hf") model = PeftModel.from_pretrained(base_model, "KalbeDigitalLab/alpara-7b-peft") - Notebooks
- Google Colab
- Kaggle
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AlpaRA 7B, a model for medical dialogue understanding. Fine-tuned using the Alpaca configuration on a curated 5,000-instruction dataset capturing nuances in patient-doctor conversations. Use Parameter Efficient Fine Tuning (PEFT) and Low Rank Adaptation (LoRA), make this model efficient on consumer-grade GPUs.
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## How to Use :
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## Load the
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```python
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from peft import PeftModel
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AlpaRA 7B, a model for medical dialogue understanding. Fine-tuned using the Alpaca configuration on a curated 5,000-instruction dataset capturing nuances in patient-doctor conversations. Use Parameter Efficient Fine Tuning (PEFT) and Low Rank Adaptation (LoRA), make this model efficient on consumer-grade GPUs.
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## How to Use :
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## Load the AlpaRA model
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```python
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from peft import PeftModel
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