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Hi everyone,
First of all let me say a big "THANK YOU" for your work !
I have successfully fine tuned phi-2. However I noticed the following:
- Inferencing with the fused model usually gives …
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Dear author,
Thank you for your significant contribution to the community; the performance of your model is truly impressive. I am curious to know if you have considered replacing the text-guided S…
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# The Power of Scale for Parameter-Efficient Prompt Tuning | LJL'Blog
还没写呢,明天再写QAQ。
[https://ljl0222.github.io/posts/prompt-tuning/](https://ljl0222.github.io/posts/prompt-tuning/)
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![image](https://github.com/user-attachments/assets/1231e002-8c11-4251-bba2-1fb02a067007)
Hi!
I am fine-tuning LLaMA3 on the hh-rlhf dataset using SimPo and noticed that the reward/chosen rewar…
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Follow the steps in prompt_yolo_world.md to finetune yolo-world-s in coco dataset, the validation map can not improve during the training process. More specifically, the validation map in epoch 5 is …
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Context
**What are you trying to do and how would you want to do it differently? Is it something you currently you cannot do? Is this related to an issue/problem?**
**Answer:** Trying to model t…
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I rush into the same question like before, #71 , #78 .
I modify the config in configs/prompt_tuning_coco/, generate custom embedding file, to fine-tune my dataset which has 4 categories.
When infer…
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I'm having difficulty understanding how to approach prompt-related performance tuning due to ambiguity on how TensorRT's prefix caching works.
My current understanding of prefix caching as implemen…
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[paper](https://arxiv.org/pdf/2104.08691.pdf)
[code](https://github.com/google-research/prompt-tuning)
[code2](https://github.com/google-research/text-to-text-transfer-transformer/blob/main/released…
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### Feature request
Training code implementation for finetuning Whisper using prompts.
Hi All,
I’m trying to finetune Whisper by resuming its pre-training task and adding initial prompts as pa…