Comments (3)
This requires a HuggingFace format model.
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If you are talking about model quantization other than OPT, BLOOM, and LLaMa,
See IST-DASLab/gptq#3.
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Just LLaMA.
I found this:
python llama.py C:\Users\lxe\text-generation-webui\models\llama-7b c4 --wbits 4 --save llama-7b-4bit.pt
But it's unclear to me. Is the input for this script the original .pth format model from Facebook or the HuggingFace format model?
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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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