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drbh 04e1af94d7
Enable multiple LoRa adapters (#2010) 
* feat: first draft load multiple lora

* feat: load weights within layer and refactor lora pass

* fix: refactor and reduce lora math

* feat: baseline impl single request multi lora support

* feat: prefer lorax implementation and port loading logic

* fix: prefer adapter_data and refactors

* feat: perfer loraxs custom punica kernels and add mlp loras

* fix: adjust batch for bgmv

* fix: adjust adapter_segments logic when in batch

* fix: refactor and move changes to v3 proto

* fix: pass model_id for all flash causal lms

* fix: pass model_id for all causal and seq2seq lms

* fix: add model_id to model test

* feat: add lora support to mistral and refactors

* feat: prefer model id in request

* fix: include rust code for adapter id

* feat: bump launcher and add new lora docs

* feat: support base model generation and refactors

* fix: rename doc to retry ci build

* feat: support if vlm models

* fix: add adapter_data param and avoid missing layers

* fix: add adapter_data param to phi and neox

* fix: update all models forwards to include adapter_data

* fix: add model_id to IdeficsCausalLM

* Update lora.md

Fixed a typo

* Update lora.md

Fixing spam image

* fix: add lora kernel to dockerfile, support running without kernels and refactors

* fix: avoid dockerfile conflict

* fix: refactors and adjust flash llama lora logic

* fix: skip llama test due to CI issue (temp)

* fix: skip llama test CI (temp) 2

* fix: revert skips and prefer updated ci token for tests

* fix: refactors and helpful comments

* fix: add noop in TensorParallelAdapterRowLinear too

* fix: refactor and move shard_lora_weights logic

* fix: exit early if no adapter_data

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Co-authored-by: Derek <datavistics@gmail.com>
 		2024-06-25 14:46:27 -04:00
..
src Enable multiple LoRa adapters (#2010) 2024-06-25 14:46:27 -04:00
Cargo.toml Upgrading all versions. (#1759) 2024-04-18 17:17:40 +02:00
README.md
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README.md

Text Generation Inference benchmarking tool

benchmark

A lightweight benchmarking tool based inspired by oha and powered by tui.

Install

make install-benchmark

Run

First, start text-generation-inference:

text-generation-launcher --model-id bigscience/bloom-560m

Then run the benchmarking tool:

text-generation-benchmark --tokenizer-name bigscience/bloom-560m