Comments (1)
Hi MaCask, megatron mainly focuses on Homogenous training setting as you rightly pointed since heterogenous is quite rare. Its not on our roadmap either in the short term.
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Related Issues (20)
- [QUESTION] Training Llama3 70B on 16 x A100 only achieves low throughput of 20 TFLOPS HOT 1
- [QUESTION]Why is the operator of computation slower when computation overlaps with communication
- [QUESTION] Will the data get re-shuffled if the sequence length is modified during training?
- [BUG] bugs when using pytorch2.4.0 to run run_simple_mcore_train_loop.py HOT 1
- [BUG] T5 extended attention mask shape mismatch with transformer engine HOT 5
- [QUESTION] How to save model trained by TP=8 and load model in TP=4 or other? HOT 1
- [BUG] "builders[key].finalize(...)" only finalize the last key after the loop in the "preprocess_data.py"
- [QUESTION] I found that the Huggingface Tokenizer cannot be selected in Date Preprocessing. Is this intentional or a bug?
- [BUG] `finish_embedding_wgrad_compute` appears after grad all-reduce HOT 1
- [QUESTION] glu activation with tensor parallel in GroupedMLP HOT 2
- [BUG] arguments of get_cpu_offload_context() in transformer_engine.py for different version of te HOT 4
- [QUESTION] Does it support Knowledge Distillation? HOT 1
- No pre-norm for non-moe gpt style model when using TE-transformer layer spec??? HOT 2
- [BUG] clip key mismatch HOT 1
- [BUG] error raised while converting llm to megatron
- FASE 6 LILITI STK 3.6.9 INTELIGÊNCIA ARTIFICIAL ANTI CARBONO.
- [QUESTION] How to freeze specific modules while training? HOT 1
- [QUESTION] Why and When dose matmul call different kernels? HOT 1
- [BUG] llava pipeline parallel initialization problem HOT 1
- Why is gather_output not supported in ColumnParallelLinear when using sequence parallelism?
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