Comments (1)
@larry-fuy there are no immediate plans to support these models, but we are very welcome to outside contributions. Our documentation could certainly be improved in terms of describing how to add new model support, so let me provide a starting point here and I would be happy to help in the process.
In general, to support a model we need to have support for kernel injection on the DeepSpeed-inference side (but we can also run models without kernel injection if we only want to use ZeRO). For example, we support automatic kernel injection with Bert
, GPT-J
, etc. models with DeepSpeed-inference. Kernel injection can also be achieved with custom injection policies. Check out this example from our unit tests on how to do this:
https://github.com/microsoft/DeepSpeed/blob/62c071e016aca6dbf12695bdb680721dcf3500ad/tests/unit/inference/test_inference.py#L408
Once we have this support on the DeepSpeed-inference side, adding the model to MII should be as easy as expanding the list of supported model types and tasks.
Please let me know if I can clarify anything further.
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Related Issues (20)
- Base model support HOT 1
- Support for Codellama Model in deepspeed-fastgen HOT 2
- Invalid parameter bricks service HOT 1
- Deadlock detected HOT 5
- AttributeError: 'NoneType' object has no attribute 'value' HOT 2
- RuntimeError: There is no current event loop in thread 'Thread-1'. HOT 2
- support chatglm3 HOT 1
- Loading Bloom-3b in persisten mode fails HOT 1
- restful api host need configuration HOT 1
- Can deepspeed-MII run on AMD GPU? HOT 2
- The choice of the split size for splitAndFuse HOT 4
- How to stream tokens? HOT 1
- Error messages spilled from persistent deployment for every request HOT 6
- Can you support DeepSeek's inference acceleration? Thank you very much. HOT 2
- mixtral support HOT 2
- Deployment in kubernetes
- Reproduced readme results HOT 8
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- Problem while running facebook/opt-125m with MII HOT 2
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