extra: Add benchmark script implemented in Python (#1298)

* Create bench.py

* Various benchmark results

* Update benchmark script with hardware name, and file checks

* Remove old benchmark results

* Add git shorthash

* Round to 2 digits on calculated floats

* Fix the header reference when sorting results

* FIx order of models

* Parse file name

* Simplify filecheck

* Improve print run print statement

* Use simplified model name

* Update benchmark_results.csv

* Process single or lists of processors and threads

* Ignore benchmark results, dont check in

* Move bench.py to extra folder

* Readme section on how to use

* Move command to correct location

* Use separate list for models that exist

* Handle subprocess error in git short hash check

* Fix filtered models list initialization

README.md

@@ -709,6 +709,19 @@ took to execute it. The results are summarized in the following Github issue:
 
 [Benchmark results](https://github.com/ggerganov/whisper.cpp/issues/89)
 
+Additionally a script to run whisper.cpp with different models and audio files is provided [bench.py](bench.py).
+
+You can run it with the following command, by default it will run against any standard model in the models folder.
+
+```bash
+python3 extra/bench.py -f samples/jfk.wav -t 2,4,8 -p 1,2
+```
+
+It is written in python with the intention of being easy to modify and extend for your benchmarking use case.
+
+It outputs a csv file with the results of the benchmarking.
+
+
 ## ggml format
 
 The original models are converted to a custom binary format. This allows to pack everything needed into a single file: