adaptnlp
Basic-UI-for-GPT-J-6B-with-low-vram
| adaptnlp | Basic-UI-for-GPT-J-6B-with-low-vram | |
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| 2 | 4 | |
| 414 | 113 | |
| 0.0% | - | |
| 0.0 | 0.0 | |
| over 2 years ago | over 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | Apache License 2.0 |
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adaptnlp
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Tools to use for Semantic-searching Question Answering System
Check out adaptnlp
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Case Sensitivity using HuggingFace & Google's T5 model (base)
Yes, there are capitals in the tokenizer vocabulary of t5-base and t5-small, so both support capitalization. A few days ago I was using t5-small through adaptnlp for extractive summarization and capitalization was working fine (https://github.com/Novetta/adaptnlp). AdaptNLP is basically just a transformers wrapper, so if you can't figure out a solution, you could just dissect their source code.
Basic-UI-for-GPT-J-6B-with-low-vram
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How to run this service with a local GPU?
You need a lot of VRAM to run the AI models, scaling somewhat with the amount of parameters a model uses. The most advanced model Pygmalion has is 6 billion parameters, which requires a minimum of 16GB of VRAM to run locally at decent speeds. There are methods of running 6b locally on low VRAM machines as listed here: https://github.com/arrmansa/Basic-UI-for-GPT-J-6B-with-low-vram but even then, the generations would be excruciatingly slow, and the lowest VRAM card used with this method has 6GB of VRAM.
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Tesla M40 and GPT-J-6B
While waiting however I came across https://github.com/arrmansa/Basic-UI-for-GPT-J-6B-with-low-vram which allows you to use some of system memory to run the model. I was able to get a version working with 2.7B on my 2060 6GB with KoboldAI. The github above has an error that prevents it from working (https://github.com/arrmansa/Basic-UI-for-GPT-J-6B-with-low-vram/issues/1), but other than that it works.
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How is any of this even possible?
Just to add to this, there is a low VRAM version of GPT-J here (suggest 16GB RAM + 8GB GPU).
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GPT-J 6B locally on my computer
I found this yesterday, is it somehow possible to use this with KoboldAI to run GPT-J on weaker graphics cards?
What are some alternatives?
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