Comments (2)
feliperafael
commented on August 14, 2024
Probably your issue really is a lack of memory, since the minimum required to run this model (with 7 billion parameters) is around 12gb of VRAM (GPU RAM memory). You can try using GPUs from google colab, or use a computer with at least 32gb of RAM and a video card with at least 12gb of VRAM
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matthsena
commented on August 14, 2024
I was having the same problem trying to fine tune the alpaca-lora, to solve it i had to subscribe to Colab Pro to use more powerful GPUs and more RAM. I didn't try to run the cabrita-lora.ipynb before that, but try to run it in the free version of Colab, if you get an error the solution may be the same one I took
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Related Issues (14)
- Translation from English + Finetuning vs. original LLama quality HOT 3
- Did not find branch or tag 'c3dc391', assuming revision or ref. HOT 2
- Questioning the Cost of Data translation with ChatGPT Turbo HOT 10
- Can't find config.json at '{pretrained_model_name_or_path} HOT 1
- Translation scripts stops after a few minutes HOT 7
- I am getting error at "from transformers import AutoTokenizer, AutoConfig, LLaMAForCausalLM, LLaMATokenizer" HOT 2
- Out of memory HOT 1
- Cannot copy out of meta tensor; no data!
- About the training time on Google Colab A100
- Any unquantized and quantized models available? HOT 1
- Alteração nos imports LLaMAForCausalLM e LLaMATokenizer
- Tokenizer bug on dictionary
- Quantos seria necessário para uma tradução por Brasileiros
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