While we focus on a simple yet effect setup, namely adapting only theqandvprojection in a Transformer, in our examples, LoRA can be apply to any subsets of pre-trained weights. We encourage you to explore different configurations, such as adapting the embedding layer by replacingnn.Embeddingwi...
alpha_pattern (dict)— The mapping from layer names or regexp expression to alphas which are different from the default alpha specified by lora_alpha. For example, {'^model.decoder.layers.0.encoder_attn.k_proj': 16}. 这两个参数则是用来定制化设定 lora的rank和lora alpha的,具体可见上面的例子...
{ "alpha_pattern": {}, "auto_mapping": null, "base_model_name_or_path": "./ms_cache/hub/Qwen/Qwen2-VL-7B-Instruct", "bias": "none", "fan_in_fan_out": false, "inference_mode": true, "init_lora_weights": true, "layer_replication": null, "layers_pattern": null, "layers_...
While we focus on a simple yet effect setup, namely adapting only theqandvprojection in a Transformer, in our examples, LoRA can be apply to any subsets of pre-trained weights. We encourage you to explore different configurations, such as adapting the embedding layer by replacingnn.Embeddingwi...
If the LoRA seems to have too much effect (i.e., overfitted), set alpha to lower value. If the LoRA seems to have too little effect, set alpha to higher than 1.0. You can tune these values to your needs. This value can be even slightly greater than 1.0! Example $ lora_add ...
The PDR for different configurations of satellites. There are three layers that satellites can be on. The x axis shows the configuration of the two transmitter satellites. 1 corresponds to the lowest layer, and 3 corresponds to the highest layer. The PDR is much greater when both satellites ...
Table 6: LoRA-X subspace constraint effect on transferability of style adapter. BlueFire dataset, SD-v1.5 as the source model and SD Eff-v1.0 as the target. Method Adapter Rank HPSv2 (↑) LPIPS diversity (↑) DINOv2 (↑) Total size (MB) LoRA-X Trained 320 0.2958 0.5340 0.8513 0.16...
Therefore, assigning the same rank to LoRA modules of different layers is not the optimal choice. It is better to adaptively allocate ranks to LoRA modules of different layers. Existing methods adaptively ...
In contrast, our simulator has been developed for the sake of completeness and it is oriented towards an accurate representation of the LoRaWAN at the different layers. After a detailed description of the simulator, we report a validation of the simulator itself and we then conclude by ...
Then the next row is INS+MID, MID+MID, OUTD+MID, and so on. Example image here Effective Block Analyzer This function check which layers are working well. The effect of the block is visualized and quantified by setting the intensity of the other bocks to 1, decreasing the intensity of ...