Comments (4)
Seems to be resolved now
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@drnikolaev or @borisfom any ideas on what the problem is here?
from nemo.
See #253
from nemo.
Thanks gang ! it builds and works perfect now on our k8s cluster !
from nemo.
Related Issues (20)
- Why use two types of names? spe refers to the Google sentencepiece library tokenizer. bpe for SentencePiece tokenizer HOT 2
- Error in coverting Mixtral-7B hf checkpoint to Nemo HOT 1
- Error while exporting to TensorRTLLM format - AttributeError: 'NoneType' object has no attribute 'get' HOT 3
- `megatron_gpt_finetuning.py` does not work `max_epochs` HOT 1
- Is frame marblenet VAD still supported?
- Context parallel does not work in some cases which works well using megatron-lm directly
- Can't train/finetune a model on two RTX4090
- is Forced Alignment available on prebuilt Docker images? HOT 1
- Support for Specifying Start and End Time when Reading WAV File HOT 1
- Saving and reloading the pretrained model's vocab breaks the tokenizer.
- IndexError: index -1 is out of bounds for dimension 1 with size 0
- Support required for fine tuning cache aware streaming model
- Canary model stuck in a loop? Just repeats the same phrases over and over. HOT 1
- Slow training on Mixtral-8x22B when DP size > 1 HOT 2
- TypeError: EncDecRNNTBPEModel.change_vocabulary() got an unexpected keyword argument 'new_vocabulary' HOT 1
- Memory Allocation Error during alignement (tools/nemo_forced_aligner/align.py)
- "greedy_batched" methods should support "partial_hypotheses" option
- problem in exp_manager
- ImportError: cannot import name '_is_local_file_protocol' from 'pytorch_lightning.callbacks.model_checkpoint' HOT 1
- "FileNotFoundError: KenLM binary file not found at : None" thrown when decoding without N-gram LM
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