Update workers_vs_schedulers.md

docs/workers_vs_schedulers.md

@@ -2,7 +2,7 @@
 Tesseract.js offers 2 ways to run recognition jobs: (1) using a worker directly, or (2) using a scheduler to run jobs on multiple workers in parallel.  The syntax for the latter is more complicated, but using parallel processing via schedulers provides significantly better performance for large jobs.  For more detailed documentation on each function, see the [api page](./api.md). 
 
 # Option 1: Using Workers Directly
-Tesseract.js also supports creating and managing workers (the objects that execute recognition) manually. 
+The following snippet recognizes text from an image using a single worker.
 
 ```
 (async () => {
@@ -48,4 +48,4 @@ const workerN = 4;
 
 While using schedulers is no more efficient for a single job, they allow for quickly executing large numbers of jobs in parallel. 
 
-When working with schedulers, note that workers added to the same scheduler should all be homogenous—they should have the same language be configured with the same parameters.  Schedulers assign jobs to workers in a non-deterministic manner, so if the workers are not identical then recognition results will depend on which worker the job is assigned to. 
+When working with schedulers, note that workers added to the same scheduler should all be homogenous—they should have the same language be configured with the same parameters.  Schedulers assign jobs to workers in a non-deterministic manner, so if the workers are not identical then recognition results will depend on which worker the job is assigned to.