Commit Graph
22 Commits
Author SHA1 Message Date
Harry Mellor 6223dd8114 Update deprecated type hinting in model_executor/layers (#18056)
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
2025-05-13 04:17:23 -07:00
Harry Mellor 13698db634 Improve configs - ModelConfig (#17130)
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
2025-04-30 10:38:22 +08:00
Kyle Sayers 12913d17ba [Quant] Add SupportsQuant to phi3 and clip (#13104) 2025-02-15 19:28:33 -08:00
Russell Bryant e489ad7a21 [Misc] Add SPDX-License-Identifier headers to python source files (#12628)
- **Add SPDX license headers to python source files**
- **Check for SPDX headers using pre-commit**

commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745
Author: Russell Bryant <rbryant@redhat.com>
Date:   Fri Jan 31 14:18:24 2025 -0500

    Add SPDX license headers to python source files
    
This commit adds SPDX license headers to python source files as
recommended to
the project by the Linux Foundation. These headers provide a concise way
that is
both human and machine readable for communicating license information
for each
source file. It helps avoid any ambiguity about the license of the code
and can
    also be easily used by tools to help manage license compliance.
    
The Linux Foundation runs license scans against the codebase to help
ensure
    we are in compliance with the licenses of the code we use, including
dependencies. Having these headers in place helps that tool do its job.
    
    More information can be found on the SPDX site:
    
    - https://spdx.dev/learn/handling-license-info/
    
    Signed-off-by: Russell Bryant <rbryant@redhat.com>

commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea
Author: Russell Bryant <rbryant@redhat.com>
Date:   Fri Jan 31 14:36:32 2025 -0500

    Check for SPDX headers using pre-commit
    
    Signed-off-by: Russell Bryant <rbryant@redhat.com>

---------

Signed-off-by: Russell Bryant <rbryant@redhat.com>
2025-02-02 11:58:18 -08:00
Michael Goin 399c798608 Remove ScaledActivation for AWQ (#10057)
Signed-off-by: mgoin <michael@neuralmagic.com>
2024-11-06 14:27:06 +00:00
Cyrus LeungandIsotr0py c18e1a3418 [VLM] Enable overriding whether post layernorm is used in vision encoder + fix quant args (#9217)
Co-authored-by: Isotr0py <2037008807@qq.com>
2024-10-23 11:27:37 +00:00
Dipika Sikka b1e5afc3e7 [Misc] Update awq and awq_marlin to use vLLMParameters (#7422) 2024-08-13 17:08:20 -04:00
Robert Shaw 683e3cb9c4 [ Misc ] fbgemm checkpoints (#6559) 2024-07-20 09:36:57 -07:00
Dipika Sikka 7836fdcc11 [Misc] Fix get_min_capability (#5971) 2024-06-30 20:15:16 +00:00
Cody Yu a62aaf1df5 [Misc][Refactor] Generalize linear_method to be quant_method (#4373) 2024-04-26 16:41:14 -04:00
James Flemingandmgoin 2b7949c1c2 AQLM CUDA support (#3287)
Co-authored-by: mgoin <michael@neuralmagic.com>
2024-04-23 13:59:33 -04:00
Antoni Baum a10d3056da [Core] Set linear_weights directly on the layer (#3977) 2024-04-11 16:35:51 -04:00
Kunshang Ji e9da5a40c6 [Misc] Add indirection layer for custom ops (#3913) 2024-04-10 20:26:07 -07:00
Zhuohan Li 2f8844ba08 Re-enable the 80 char line width limit (#3305) 2024-03-10 19:49:14 -07:00
RexandChunan Zeng 563836496a Refactor 2 awq gemm kernels into m16nXk32 (#2723)
Co-authored-by: Chunan Zeng <chunanzeng@Chunans-Air.attlocal.net>
2024-02-12 11:02:17 -08:00
Kunshang JiandJiang Li 96b6f475dd Remove hardcoded device="cuda" to support more devices (#2503)
Co-authored-by: Jiang Li <jiang1.li@intel.com>
Co-authored-by: Kunshang Ji <kunshang.ji@intel.com>
2024-02-01 15:46:39 -08:00
Casper beb89f68b4 AWQ: Up to 2.66x higher throughput (#2566) 2024-01-26 23:53:17 -08:00
CHU Tianxiang 0fbfc4b81b Add GPTQ support (#916) 2023-12-15 03:04:22 -08:00
Yanming W e0c6f556e8 [Build] Avoid building too many extensions (#1624) 2023-11-23 16:31:19 -08:00
Simon Mo 5ffc0d13a2 Migrate linter from pylint to ruff (#1665) 2023-11-20 11:58:01 -08:00
Woosuk Kwon 8d17774f92 Add AWQ support for all models (#1714) 2023-11-18 17:56:47 -08:00
Zhuohan Li 7076fa1c9f TP/quantization/weight loading refactor part 2 - Refactor quantized linear logic and extend quantization support to all models (#1622)
Refactor the tensor parallelism, quantization, and weight-loading codes.

Summary of the new features enabled by this PR:
- **All models** are able to be quantized with AWQ and SqueezeLLM, and [soon GPTQ](https://github.com/vllm-project/vllm/pull/1580).
- Model loading code became much simpler.
- Support model parallelism for all MQA/GQA models when the number of key/value heads is smaller than the tensor parallel size.
2023-11-15 22:50:41 -08:00