Comments (2)
Which version of files are you using? I've done several updates on them.
And are those 2 parts replaced?
You can also try load the model using load_llama_model_4bit_low_ram.
And also I'll upload an inference example / training example later.
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Using your examples I was able to get it to run!
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Related Issues (20)
- How to use inference.py after finetune.py? HOT 2
- LoRA Output Identical to Base Model HOT 4
- Flash Attention 2 HOT 1
- Error attempting to finetune llama2-70b HOT 5
- High perplexity while lower loss after LoRA finetuning (how?) HOT 5
- Targeting all layers and biases HOT 2
- Feature request: Stop when loss reaches X HOT 1
- Is alpaca_lora_4bit@winglian-setup_pip missing finetune.py? HOT 1
- Unable to Build Wheels HOT 8
- Merging LoRA after finetune HOT 1
- OOM on inference while i can finetune with more tokens HOT 2
- module 'alpaca_lora_4bit.quant_cuda' has no attribute 'vecquant4recons_v2' HOT 4
- ValueError: Target module Autograd4bitQuantLinear() is not supported. HOT 7
- 3 errors detected in the compilation of "src/alpaca_lora_4bit/quant_cuda/quant_cuda_kernel.cu" HOT 2
- docker.io/nvidia/cuda:11.7.0-devel-ubuntu22.04 not available anymore HOT 1
- Finetuning CodeLLaMA34B - RuntimeError: The size of tensor a (1024) must match the size of tensor b (8192) HOT 3
- AttributeError: 'dict' object has no attribute 'to_dict' HOT 1
- trying to get this working with text-generation-webui HOT 9
- Why lora support is only for simple lora with only q_proj and v_proj ? HOT 1
- Support for moe model? HOT 2
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