Neko-Institute-of-Science
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README.md
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@@ -10,8 +10,12 @@ https://github.com/oobabooga/text-generation-webui
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ATM I'm using 2023.05.04v0 of the dataset and training full context.
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# How to test?
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1. Download LLaMA-
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2. Replace special_tokens_map.json and tokenizer_config.json using the ones on this repo.
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3. Rename LLaMA-30B-HF to vicuna-30b
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4. Load ooba: ```python server.py --listen --model vicuna-30b --load-in-8bit --chat --lora checkpoint-xxxx```
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ATM I'm using 2023.05.04v0 of the dataset and training full context.
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# Notes:
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So im only training 1 epoch as full context 30b takes a long time to train.
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My 1 epoch will take me 8 days lol but lucly the LoRA feels fully functinal at epoch 1 as shown on my 13b one.
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# How to test?
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1. Download LLaMA-30B-HF: https://huggingface.co/Neko-Institute-of-Science/LLaMA-30B-HF
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2. Replace special_tokens_map.json and tokenizer_config.json using the ones on this repo.
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3. Rename LLaMA-30B-HF to vicuna-30b
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4. Load ooba: ```python server.py --listen --model vicuna-30b --load-in-8bit --chat --lora checkpoint-xxxx```
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