Commits · 4d6ada947c7e6379b6857bc9a9a1203679d32039 · OpenDAS / vllm_cscc

09 Jul, 2024 1 commit

[CORE] Adding support for insertion of soft-tuned prompts (#4645) · 4d6ada94

Swapnil Parekh authored Jul 09, 2024


Co-authored-by: Swapnil Parekh <swapnilp@ibm.com>
Co-authored-by: Joe G <joseph.granados@h2o.ai>
Co-authored-by: Antoni Baum <antoni.baum@protonmail.com>

4d6ada94

15 Jun, 2024 1 commit
- [mypy] Enable type checking for test directory (#5017) · 0e9164b4
  Cyrus Leung authored Jun 15, 2024
  
  0e9164b4
07 Jun, 2024 1 commit
- [Core] Change LoRA embedding sharding to support loading methods (#5038) · ccdc490d
  Antoni Baum authored Jun 06, 2024
  
  ccdc490d
28 May, 2024 1 commit
- [Core] Consolidate prompt arguments to LLM engines (#4328) · 5ae5ed1e
  Cyrus Leung authored May 29, 2024
```
Co-authored-by: Roger Wang <ywang@roblox.com>
```
  5ae5ed1e
18 May, 2024 1 commit

[Lora] Support long context lora (#4787) · 2e9a2227

SangBin Cho authored May 18, 2024

Currently we need to call rotary embedding kernel for each LoRA, which makes it hard to serve multiple long context length LoRA. Add batched rotary embedding kernel and pipe it through.

It replaces the rotary embedding layer to the one that is aware of multiple cos-sin-cache per scaling factors.

Follow up of https://github.com/vllm-project/vllm/pull/3095/files

2e9a2227