do not allow using base model directly, seems that it will break things
2f0a0ce
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test new defaults
d50497e
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update ui
414c86a
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inference beams default to 2 since it’s better
bd922de
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ok
e200f8c
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why
4354315
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fix wrong Pillow version on colab
d954ae1
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try
50ba9ae
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Revert "try to fix AttributeError: module 'PIL.Image' has no attribute 'Resampling'"
1a12f0b
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try to fix AttributeError: module 'PIL.Image' has no attribute 'Resampling'
d74655a
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update README.md
d06bf26
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Merge branch 'dev-2'
6c08b63
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rename project
bbdf699
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add templates/user_and_ai.json
faa8dd3
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move to latest working version of peft
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cache lora models
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load base model on start
fa0947b
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fix inference prompt preview not updated to the latest version
e3a5631
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resolve generation canceling issue
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report status while finetune starting
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auto select prompt template for model
517781a
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save train info with model
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clear cache after training
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update README.md
4c02e18
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fix “AttributeError: module 'PIL.Image' has no attribute 'Resampling'”
60ce564
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cache loaded_base_model_with_lora
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update requirements.lock.txt
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latest peft makes model.save_pretrained in finetune.py save a 443 B adapter_model.bin which is clearly incorrect (normally adapter_model.bin should > 16 MB)
7dd8f96
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update requirements.lock.txt
3391607
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update requirements.lock.txt
19e630b
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try to lock requirements
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fix
b9929ef
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Merge branch 'main' of github.com:zetavg/llama-lora