Comments (7)
this impacts both 4-bit and 3-bit quantization
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I was able to fix this by removing line 142 from file quant.py, which sets self.bias. self.bias isn't even used in that function, so this line is unnecessary, and bias is None on pretty much every layer for this model.
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This is because llama uses a linear layer with bias set to False.
This is an easily fixable problem by changing that line as you said.
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i solved it.
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@qwopqwop200 sorry for pinging you here, but I just wanted to ask - how much VRAM would a 3-bit version of LLAMA-30B require (e.g. can it run on 16GB VRAM), and would it be fast enough (like at least a few tokens per second) on e.g. RTX A4000?
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If you do 3-bit quantization, it seems to consume about 14gb of memory at 30B. The inference rate is expected to be less than 0.1s/token.
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@qwopqwop200 wow, thanks for all of your efforts, that's amazing! I can tolerate accuracy loss as it'll still be much better than 4-bit LLAMA 13b.
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Related Issues (20)
- llama_inference 4bits error
- inference with the saved model error: AttributeError: module 'torch.backends.cuda' has no attribute 'sdp_kernel' HOT 2
- Could not obtain official perplexity using bloom_eval()
- can it support openllama model?
- Issue with GPTQ HOT 1
- High PPL when groupsize != -1 for OPT model after replace linear layer with quantlinear. HOT 1
- Help: Quantized llama-7b model with custom prompt format produces only gibberish HOT 1
- Why does the model quantization prompt KILLED at the end? HOT 2
- Would GPTQ be able to support LLaMa2? HOT 1
- Can i quantize HF version of llama model
- Transformers broke again (AttributeError: 'GPTQ' object has no attribute 'inp1') HOT 1
- LoRa and diff with bitsandbytes
- neox.py needs to add "import math"
- error: block with no terminator, has llvm.cond_br %5624, ^bb2, ^bb3
- Support Mistral.
- Syntax changed in triton.testing.do_bench() causing error when running llama_inference.py
- datasets.utils.info_utils.ExpectedMoreSplits: {'validation'} HOT 1
- Error when load GPTQ model
- GPTQ vs bitsandbytes
- add support for minicpm
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