Comments (7)
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remind @aarnphm @ssheng @parano
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Recently, I noticed that you published a blog post https://bentoml.com/blog/benchmarking-llm-inference-backends that mentioned LMDeploy currently does not support a wide variety of models yet. And this will continue to be developed, including subsequent support for MOE models on TurboMind and decoupling model and batch. The performance advantage will also be maintained, and I also look forward to your future plans. Cheers.
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Related Issues (20)
- feat: support enforce_eager option from cli HOT 1
- bug: Cannot Run an OpenLLM server regardless of where I try to get it from or what model I use HOT 6
- bug: Attempting to invoke OpenLLM from Langchain results in error HOT 2
- Availability of the OpenAI /v1/completions API Endpoint ? HOT 3
- feat: Include starcoder2
- How to deploy a model using a single machine multi card approach? HOT 1
- Deprecation Warning for PyTorch Backend HOT 2
- FileNotFoundError: [Errno 2] No such file or directory: b'/root/bentoml/models/pt-google--gemma-7b-it/latest'
- feat: c4ai-command-r-v01 support HOT 3
- feat: support Qwen1.5 HOT 2
- feat: any plan to support NPU HOT 1
- bug: An exception occurred while instantiating runner 'llm-mistral-runner' HOT 2
- bug: Not enough data for satisfy transfer length header HOT 3
- feat: Can you support llama3? HOT 3
- bug: WARNING: openllm 0.4.44 does not provide the extra 'gemma' HOT 1
- bug: error coming up while install the vllm using pip install "openllm[vllm]" HOT 1
- For AMD/GPU, how to use multi GPUS in the api_server.py HOT 2
- bug: pip package version ssues
- feat: Multimodal LLMs? HOT 1
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