
Based on a request by @mgoin , with @kylesayrs we have added an example doc for int4 w4a16 quantization, following the pre-existing int8 w8a8 quantization example and the example available in [`llm-compressor`](https://github.com/vllm-project/llm-compressor/blob/main/examples/quantization_w4a16/llama3_example.py) FIX #n/a (no issue created) @kylesayrs and I have discussed a couple additional improvements for the quantization docs. We will revisit at a later date, possibly including: - A section for "choosing the correct quantization scheme/ compression technique" - Additional vision or audio calibration datasets --------- Signed-off-by: Brian Dellabetta <bdellabe@redhat.com> Co-authored-by: Michael Goin <michael@neuralmagic.com>
20 lines
290 B
Markdown
20 lines
290 B
Markdown
(quantization-index)=
|
|
|
|
# Quantization
|
|
|
|
Quantization trades off model precision for smaller memory footprint, allowing large models to be run on a wider range of devices.
|
|
|
|
:::{toctree}
|
|
:caption: Contents
|
|
:maxdepth: 1
|
|
|
|
supported_hardware
|
|
auto_awq
|
|
bnb
|
|
gguf
|
|
int4
|
|
int8
|
|
fp8
|
|
quantized_kvcache
|
|
:::
|