Bump package version

README.md

@@ -30,7 +30,6 @@ It only uses models where necessary, which improves speed and accuracy.
 | [Switch Transformers](https://arxiv.org/pdf/2101.03961.pdf)           | arXiv paper | [View](https://github.com/VikParuchuri/marker/blob/master/data/examples/marker/switch_transformers.md) | [View](https://github.com/VikParuchuri/marker/blob/master/data/examples/nougat/switch_transformers.md) |
 | [Multi-column CNN](https://arxiv.org/pdf/1804.07821.pdf)              | arXiv paper | [View](https://github.com/VikParuchuri/marker/blob/master/data/examples/marker/multicolcnn.md)         | [View](https://github.com/VikParuchuri/marker/blob/master/data/examples/nougat/multicolcnn.md)         |
 
-
 ## Performance
 
 ![Benchmark overall](data/images/overall.png)
@@ -39,6 +38,14 @@ The above results are with marker and nougat setup so they each take ~4GB of VRA
 
 See [below](#benchmarks) for detailed speed and accuracy benchmarks, and instructions on how to run your own benchmarks.
 
+# Commercial usage
+
+I believe in open source AI, so I want this to be as widely accessible as possible, while still funding my development/training costs.
+
+All models were trained from scratch, so they're okay for commercial usage.  The weights for the models are licensed `cc-by-nc-sa-4.0`, but I will waive that for any organization under $5M USD in gross revenue in the most recent 12-month period AND under $5M in lifetime VC/angel funding raised.
+
+If you want to remove the GPL license requirements (dual-license) and/or use the weights commercially over the revenue limit, check out the options [here](https://www.datalab.to).
+
 # Community
 
 [Discord](https://discord.gg//KuZwXNGnfH) is where we discuss future development.
@@ -64,7 +71,7 @@ pip install marker-pdf
 
 ## Optional
 
-Only needed if using `ocrmypdf` as the ocr backend.
+Only needed if using `ocrmypdf` as the ocr backend.  The `ocrmypdf` OCR option will use ocrmypdf, which includes Ghostscript, an AGPL dependency, but calls it via CLI, so it does not trigger the license provisions.  Ocrmypdf is disabled by default, and will not be installed automatically.
 
 **Linux**
 
@@ -141,16 +148,18 @@ MIN_LENGTH=10000 METADATA_FILE=../pdf_meta.json NUM_DEVICES=4 NUM_WORKERS=15 mar
 
 Note that the env variables above are specific to this script, and cannot be set in `local.env`.
 
-# Important settings/Troubleshooting
+# Troubleshooting
 
-There are some settings that you may find especially useful if things aren't working the way you expect:
+There are some settings that you may find useful if things aren't working the way you expect:
 
 - `OCR_ALL_PAGES` - set this to true to force OCR all pages.  This can be very useful if the table layouts aren't recognized properly by default, or if there is garbled text.
 - `TORCH_DEVICE` - set this to force marker to use a given torch device for inference.
 - `OCR_ENGINE` - can set this to `surya` or `ocrmypdf`.
 - `DEBUG` - setting this to `True` shows ray logs when converting multiple pdfs
+- Verify that you set the languages correctly, or passed in a metadata file.
+- If you're getting out of memory errors, decrease worker count (increased the `VRAM_PER_TASK` setting).  You can also try splitting up long PDFs into multiple files.
 
-In general, if output is not what you expect, trying to OCR the PDF is a good first step.
+In general, if output is not what you expect, trying to OCR the PDF is a good first step.  Not all PDFs have good text/bboxes embedded in them.
 
 # Benchmarks
 
@@ -201,14 +210,6 @@ This will benchmark marker against other text extraction methods.  It sets up ba
 
 Omit `--nougat` to exclude nougat from the benchmark.  I don't recommend running nougat on CPU, since it is very slow.
 
-# Commercial usage
-
-All models were trained from scratch, so they're okay for commercial usage.  The weights for the models are licensed cc-by-nc-sa-4.0, but I will waive that for any organization under $5M USD in gross revenue in the most recent 12-month period AND under $5M in lifetime VC/angel funding raised.
-
-If you want to remove the GPL license requirements for inference or use the weights commercially over the revenue limit, please contact me at marker@vikas.sh for dual licensing.
-
-Note that the `ocrmypdf` OCR option will use ocrmypdf, which includes Ghostscript, an AGPL dependency, but calls it via CLI, so it does not trigger the license provisions.  Ocrmypdf is disabled by default, and will not be installed automatically.
-
 # Thanks
 
 This work would not have been possible without amazing open source models and datasets, including (but not limited to):

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "marker-pdf"
-version = "0.2.4"
+version = "0.2.5"
 description = "Convert PDF to markdown with high speed and accuracy."
 authors = ["Vik Paruchuri <github@vikas.sh>"]
 readme = "README.md"