Comments (2)
gaopengpjlab
commented on May 27, 2024
1
We use A6000 with 48G memory for alpaca_finetuning_v1. Note that https://github.com/Lightning-AI/lit-llama only require 3090 GPU for finetuning and inference of llama-adapter.
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gaopengpjlab
commented on May 27, 2024
1
alpaca_finetuning_v2 support cpu-offload and Tensor Parallelism which can significantly reduce GPU memory requirement and split the model upon multi-gpu for training.
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Related Issues (20)
- Not able to reproduce results of llama-adapter-v2 HOT 1
- How to fine-tune the llama-adapter-v2 for llama-2 7b models. HOT 1
- I have problem with downloading 7B_chinese in imagebind_LLM. HOT 1
- The true weight file not find? HOT 4
- Could you please provide these weight with me? HOT 2
- Unable to produce the result between LLaMA-Adapter V1 and Alpaca HOT 1
- question about Pretrained LLAMA applicable to Llama_adapter model. thanks HOT 1
- I don't know which data to use to reproduce the model llama-adapter-multimodal-v2.
- Does storage space in the paper mean the capacity of checkpoint file? HOT 2
- Inquiry on Loading LLaMa-2 Model Parameters HOT 1
- how to set llama adapter max_seq_len = 4096
- [LLaMA Adapter V2] Evaluation on multiple choice questions. HOT 1
- AssertionError: Loading a checkpoint for MP=0 but world size is 1 HOT 2
- Don't find save path"ADAPTER_PATH" HOT 1
- Getting error "AF_UNIX path too long"
- Loss is nan, stopping training, while trying to reproduce alpaca_finetuning_v1 results. HOT 1
- Simple question about llama adapter v1 transformer forward function
- imagebind_LLM中的get_chinese_llama.py文件丢失，可以补充一下吗？ HOT 1
- Getting weird output for multimodal 7B adapter HOT 3
- Assertation Error start_pos- AdapterV2 Multimodal
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