Comments (4)
I believe that triton flash attention will not work on P100s. Could you try uninstalling flash_attn_triton
before running anything? I think then it will fall back to torch attention properly instead of trying to use flash attention and failing.
from examples.
Thank you for your quick response! Unfortunately I do not have a flash_attn_triton
package installed. I only find flash_attn
, but uninstalling it doesnt help.
from examples.
Apologies, I think I got the package wrong, and it's actually triton
you want to uninstall. flash_attn_triton
is a file in our repo. We have a try/catch around importing it, which would disable the triton attention implementation, but I guess for you the import succeeds and then it fails when it starts actually running. So I want to make that import fail so that triton is disabled.
from examples.
Did also not work for me unfortunately. However, I just switched to pretrain hf-bert, that works fine.
Thank you for your help!
from examples.
Related Issues (20)
- Train BERT on own data HOT 3
- Can't save a trained model as a HuggingFace model HOT 5
- Accessing model after pre-training HOT 1
- Inquiry about Mosaic-BERT and BERT-Base Sequence Lengths HOT 9
- Confusion regarding conflicting information in model card of "mosaic-bert" on Hugging Face HOT 2
- Explain composer logs emitted during training + Replicate Benchmark Results HOT 1
- Finetuning on windows machine HOT 4
- --concat_tokens flag in BERT pretraining HOT 2
- config class for bert is not consistent HOT 2
- Please bring code features from MPT-7b back to MPT-1b for use of MPT-1b with SFTTrainer.
- FlashAttention Triton error on the MosaicBERT models other than base HOT 3
- MosaicBERT: pretraining configuration for models > 128 seq. length HOT 5
- MosaicBERT: Convert composer weights to HF HOT 1
- Error when training with Mosaic-Bert
- How to add a custom key to config file?
- Matmul error when using output_all_encoded_layers = True, and pooler
- Can't install the requirements for mosaicml
- MosaicBert: Training stops after first evaluation pass with Flash Attention 2
- Finetuning Error
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