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Xiao9905 avatar Xiao9905 commented on July 20, 2024

@lomizandtyd Hi,

Thanks for your interest in GLM-130B!

Currently I'm using "[MASK]" at the end of dialogue for bot's response generation.

That's cool! Looking forward to your application online, and please contact as we can also help to promote it for you.

Your GLM repo https://github.com/THUDM/GLM reports [sMASK] could be used for sentence generation.
But I didn't find any doc in this repo. Does GLM-130 B support [sMASK] for sentence generation?

Unfortunately, we didn't implement [sMASK] in GLM-130B since it harms the efficiency of pre-training. However, we are planning to train GLM-130B for a few steps on [sMASK] objectives to enable this feature. Please wait for a few days as we are working on it : )

Do you have any plan to export more API of GLM-130 B ? Such as compute LM perplexity / Multiple choice selection or any other features? Since you have already test the model on Few-CLUE, there must be ways to utilize those features.

That sounds great. But it may not be our first priority since we are now having a hard time sparing any machines for such a goal. Thanks for your suggestions.

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lomizandtyd avatar lomizandtyd commented on July 20, 2024

Could you provide some guidelines about how to compute PPL/logprobs of input sentence on GLM-130 B?

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Sengxian avatar Sengxian commented on July 20, 2024

Hello @lomizandtyd, we have recently implemented evaluation code for language modeling tasks such as WikiText103 and PTB, you can check out the eval-lm branch and the code will be merged into the main branch after further testing. Here are our preliminary results for your reference:

WikiText-2(PPL) WikiText-103(PPL) PTB(PPL)
10.901 10.759 18.964

If you have any other questions, please feel free to ask. Thank you again for your interest in GLM-130B!

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lomizandtyd avatar lomizandtyd commented on July 20, 2024

Thanks, that's what I want.

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