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taokz / BiomedGPT

BiomedGPT: A Unified and Generalist Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks
Apache License 2.0
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Quantize Per-Trained model Using QLoRa or LoRa , PFET Technique #4

Open deep-matter opened 12 months ago

deep-matter commented 12 months ago

I would like to ask how can I use QLoRa or Parameter-Efficient Fine-Tuning thin a model does not register at Hugging face instead is Based on OFA

i am trying to Quantize the Tiny version but I don’t know if I need to use Lora in which way for Parameter-Efficient Fine-Tuning

i thought if i reconstruct the model BioMedGPT_Tiny from Unify_Transfomer.py following fie ofa.py and indicate to Config parameters to have BiomedGPT_tiny in separation file then apply Quantization Techniques but the problem is that the tokenizer Pet-Trained model not available i think

evolu8 commented 12 months ago

I'd second this. Would be wonderful to have instructions on this.