Comments (2)
Hello, thank you for your interest in our work!
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There might be a dependence on whether a reduction at a certain layer is helpful, given there is a reduction made in another layer. Therefore, we cannot just compose reductions after individually searching for the best rate per layer, while holding other layers fixed.
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Added a script that walks through our procedure for this.
We wanted to check if the benefits of performing laser across layers are additive or not, so we employed a simple strategy. The current strategy we use is as follows:
1. Initialize a vector that represents different amounts of reduction across each of the different layers
2. Edit the model with Laser starting from the final layer (restricted over a set
3. Validate over the validation set of the dataset
4. use the signal from step 2 to reduce or increase the amount of reduction
5. repeat until convergence
6. return the vector of reductions
I have also added a script that walks through this procedure under the scripts
directory.
One thing to note: This search procedure is probably not the most efficient and only performs a sparse search over possible
from laser.
MANY THANKS!!!!
from laser.
Related Issues (20)
- Excellent work, looking forward to following up with further research! HOT 3
- What is the ETA on the code HOT 2
- License HOT 6
- Mistral Support HOT 16
- Where to Get the Dataset HOT 5
- Question HOT 2
- Do you think it could work for MoE models like Mixtral? HOT 2
- Rank-reduced models? HOT 4
- Feature Request for Upcoming Refactoring
- Rank reduction using random matrix theory HOT 1
- what does the 'rate' parameters actually mean in code? HOT 2
- Potential improvements for evaluation HOT 1
- Application to three-dimensional tensors HOT 1
- Llama2-7B + TruthfulQA reproduce issue HOT 8
- Generic model? HOT 3
- how to get base model accuracy HOT 2
- Problem Encountered During Reproduction HOT 2
- How to reproduce Figure 5 analysis in this paper?
- Reproducing LLAMA-2 metrics HOT 2
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from laser.