FIX [quantization / ESM] Fix ESM 8bit / 4bit with bitsandbytes#29329
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younesbelkada merged 3 commits intohuggingface:mainfrom Mar 1, 2024
Merged
FIX [quantization / ESM] Fix ESM 8bit / 4bit with bitsandbytes#29329younesbelkada merged 3 commits intohuggingface:mainfrom
quantization / ESM] Fix ESM 8bit / 4bit with bitsandbytes#29329younesbelkada merged 3 commits intohuggingface:mainfrom
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younesbelkada
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Feb 28, 2024
| attention_probs = attention_probs * head_mask | ||
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| context_layer = torch.matmul(attention_probs, value_layer) | ||
| context_layer = torch.matmul(attention_probs.to(value_layer.dtype), value_layer) |
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This was needed to perform correctly inference otherwise you get dtype mismatch
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what do we get if we don't do this fix ?
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You get a dtype mismatch :/
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
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Thanks for the quick fix, everyone! |
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What does this PR do?
Fixes: #29323
Currently on main, simply running:
Fails with an error
This is because the model pushed in
"facebook/esm2_t36_3B_UR50D"do not contain theinv_freq. Maybe during the HfQuantizer refactor we did not properly dealt with that specific scenario, leading to this bug for transformers > 4.37cc @SunMarc
I ran the quantization tests and they seem to all pass on my end