Difference between revisions of "Free Software Directory:Artificial Intelligence Team"
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* Text generation: | * Text generation: | ||
** [[GPT-Neo]] | ** [[GPT-Neo]] | ||
| + | *** "*As of August, 2021 code is no longer maintained. It is preserved here in archival form for people who wish to continue to use it." - https://github.com/EleutherAI/gpt-neo | ||
| + | *** Still useful since it's lightweight hardware requirement: https://huggingface.co/EleutherAI/gpt-neo-125M | ||
** [[GPT-J]] | ** [[GPT-J]] | ||
*** "To load GPT-J in float32 one would need at least 2x model size CPU RAM: 1x for initial weights and another 1x to load the checkpoint. So for GPT-J it would take at least 48GB of CPU RAM to just load the model." - https://huggingface.co/docs/transformers/v4.14.1/en/model_doc/gptj | *** "To load GPT-J in float32 one would need at least 2x model size CPU RAM: 1x for initial weights and another 1x to load the checkpoint. So for GPT-J it would take at least 48GB of CPU RAM to just load the model." - https://huggingface.co/docs/transformers/v4.14.1/en/model_doc/gptj | ||
Revision as of 22:20, 24 February 2023
- Argos Translate
- Text/speech
- Text generation:
- GPT-Neo
- "*As of August, 2021 code is no longer maintained. It is preserved here in archival form for people who wish to continue to use it." - https://github.com/EleutherAI/gpt-neo
- Still useful since it's lightweight hardware requirement: https://huggingface.co/EleutherAI/gpt-neo-125M
- GPT-J
- "To load GPT-J in float32 one would need at least 2x model size CPU RAM: 1x for initial weights and another 1x to load the checkpoint. So for GPT-J it would take at least 48GB of CPU RAM to just load the model." - https://huggingface.co/docs/transformers/v4.14.1/en/model_doc/gptj
- EleutherAI: GPT-NeoX
- "Basically GPT-NeoX requires at least 42GB of VRAM and 40 GB of disk space (and yes we're talking about the slim fp16 version here)." - https://nlpcloud.com/deploying-gpt-neox-20-production-focus-deepspeed.html
- GPT-Neo
- Image creation:
- Package manager: Transformers - https://github.com/huggingface/transformers/
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