Comments (4)
@thanhlt998 releasing in this week's main branch release (today/tomorrow). Stay tuned.
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@Oldpan for now we only support static batching for encoder-decoder models. But we plan inflight batching support in the coming weeks. Please keep an eye out. Feel free to reopen the issue if you have more questions.
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@schetlur-nv do you have any progresses here?
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@symphonylyh
Thanks for the update, does this support encoders like nougat that require image inputs? I see that only bart and t5 are mentioned in the updated examples.
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Related Issues (20)
- Finding protobuf files while benchmarking TensorRT-LLM HOT 2
- How to add a new quantization method?
- How to preprocess a int4 model? HOT 1
- Does TensorRT-LLM support passing input_embeds directly? HOT 11
- Convert_checkpoint.py failed with LLAMA 3.1 8B instruct HOT 2
- Will KOSMOS-2.5 be supported?
- Assertion failed: FMHA kernels are not found
- Why are the answers the same every time?
- Conver qwen2-57B-A14B failed
- `--use_fp8_context_fmha` is broken with Llama models
- Concerns about the removal of batch manager C++ API HOT 1
- Build failure when using FP8 quantized Medusa heads
- wgmma.mma_async instructions are serialized due to non wgmma instructions defining accumulator registers of a wgmma between start and end of the pipeline stage
- The weights compiled by v0.11.0 are run using TritonServer, and the concurrency is lower than that of the v0.10.0 version. The compilation scripts are the same.
- AttributeError: 'PluginConfig' object has no attribute '_streamingllm'. Did you mean: '_streamingllm'? HOT 4
- multi_block_mode has been removed in the current version? HOT 2
- TensorRT LLM does not stop while met the eos_id
- Llama3.1 support removed? HOT 2
- Cannot support long context input vs vllm.
- torch.OutOfMemoryError when try to build TensorRT engines for Qwen2-72B(-Instruct)
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