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For smaller models, quantization causes more quality loss than large models. Could the repository try 6-bit / 128 groups for stuff like LLaMa-7B? This could be most useful for some of the smaller lang…
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I have set input sparsetensor using same coordinate_manager
` sinput1 = ME.SparseTensor(features=input_dict['sinput_s_F'].to(self.device),
coordinates=input_…
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- Paper:
[S. Wiedemann et al., "DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks," IEEE Journal of selected topics in signal processing, May 2020.](https://arxiv.org/pdf/1905.08…
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why the clip range is (-6, 60) in mobilebert quantization?
https://github.com/google-research/google-research/blob/ba74f16e2e193f62133faf73a06e7f0792d42681/mobilebert/modeling.py#L1135
The comme…
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jetson@ubuntu:~$ jetson-containers run $(autotag nano_llm) python3 -m nano_llm.chat --api=mlc --model Efficient-Large-Model/VILA1.5-3b --max-context-len 256 --max-new-tokens 32 --pro…
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This quantization scheme can speed up the inference of neural networks, but there still is less example in CNN or RCNN, even RNN.
Is these ones not easy on ggml or other reasons?
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### System Info
```Shell
- `Accelerate` version: 1.0.0
- Platform: Linux-6.8.0-47-generic-x86_64-with-glibc2.35
- `accelerate` bash location: /home/user/anaconda3/envs/accelerate_multi/bin/accelera…
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## Quantization Method for conv, deconv and fc Layers.
Here I want to implement the quanzization on operation in conv, deconv and fc layers. Much quantization method are included in this paper: Ristr…
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## Description
I am trying to figure out if TensoRT and the `pytorch_quantization` module support post-training quantization for vision transformers.
The following piece of code follows the `pyt…
RuRo updated
3 months ago
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Many neural network optimization and quantization methods may be a really good motivating example for "Chexo" because we probably never want to reason about the soundness of their numerical stability,…