Added start of FAQ for version 6.0
diff --git a/6.0/faq.md b/6.0/faq.md
new file mode 100644
index 0000000..97fc978
--- /dev/null
+++ b/6.0/faq.md
@@ -0,0 +1,124 @@
+---
+layout: default
+category: help
+title: Common questions, problems, and solutions
+---
+
+1. How do I make Joshua produce better results?
+
+ One way is to add a larger language model. Build on Gigaword, news
+ crawl data, etc. `lmplz` makes it easy to build and efficient to
+ represent (especially if you compress it with `build_binary). To
+ include it in Joshua, there are two ways:
+
+ - *Pipeline*. By default, Joshua's pipeline builds a language
+ model on the target side of your parallel training data. But
+ Joshua can decode with any number of additional language models
+ as well. So you can build a language model separately,
+ presumably on much more data (since you won't be constrained
+ only to one side of parallel data, which is much more scarce
+ than monolingual data). Once you've built extra language models
+ and compiled them with KenLM's `build_binary` script, you can
+ tell the pipeline to use them with any number of `--lmfile
+ /path/to/lm/file` flags.
+
+ - *Joshua* (directly).
+ [This file](http://localhost:4000/6.0/file-formats.html)
+ documents the Joshua configuration file format.
+
+1. I have already run the pipeline once. How do I run it again,
+ skipping the early stages and just retuning the model?
+
+ You would need to do this if, for example, you added a language
+ model, or changed some other parameter (e.g., an improvement to the
+ decoder). To do this, follow the following steps:
+
+ - Re-run the pipeline giving it a new `--rundir N+1` (where `N` is the last
+ run, and `N+1` is a new, non-existent directory).
+ - Give it all the other flags that you gave before, such as the
+ tuning data, testing data, source and target flags, etc. You
+ don't have to give it the training data.
+ - Tell it to start at the tuning step with `--first-step TUNE`
+ - Tell it where all of your language model files are with `--lmfile
+ /path/to/lm` lines. You also have to tell it where the main
+ language model is, which is usually `--lmfile N/lm.kenlm` (paths
+ are relative to the directory above the run directory.
+ - Tell it where the main grammar is, e.g., `--grammar
+ N/grammar.gz`. If the tuning and test data hasn't changed, you
+ can also point it to the filtered and packed versions to save a
+ little time using `--tune-grammar N/data/tune/grammar.packed` and
+ `--test-grammar N/data/test/grammar.packed`, where `N` here again
+ is the previous run (or some other run; it can be anywhere).
+
+ Here's an example. Let's say you ran a full pipeline as run 1, and
+ now added a new language model and want to see how it affects the
+ decoder. Your first run might have been invoked like this:
+
+ $JOSHUA/scripts/training/pipeline.pl \
+ --rundir 1 \
+ --readme "Baseline French--English Europarl hiero system" \
+ --corpus /path/to/europarl \
+ --tune /path/to/europarl/tune \
+ --test /path/to/europarl/test \
+ --source fr \
+ --target en \
+ --threads 8 \
+ --joshua-mem 30g \
+ --tuner mira \
+ --type hiero \
+ --aligner berkeley
+
+ Your new run will look like this:
+
+ $JOSHUA/scripts/training/pipeline.pl \
+ --rundir 2 \
+ --readme "Adding in a huge language model" \
+ --tune /path/to/europarl/tune \
+ --test /path/to/europarl/test \
+ --source fr \
+ --target en \
+ --threads 8 \
+ --joshua-mem 30g \
+ --tuner mira \
+ --type hiero \
+ --aligner berkeley \
+ --first-step TUNE \
+ --lmfile 1/lm.kenlm \
+ --lmfile /path/to/huge/new/lm \
+ --tune-grammar 1/data/tune/grammar.packed \
+ --test-grammar 1/data/test/grammar.packed
+
+ Notice the changes: we removed the `--corpus` (though it would have
+ been fine to have left it, it would have just been skipped),
+ specified the first step, changed the run directory and README
+ comments, and pointed to the grammars and *both* language model files.
+
+3. How can I enable specific feature functions?
+
+ Let's say you created a new feature function, `OracleFeature`, and
+ you want to enable it. You can do this in two ways. Through the
+ pipeline, simply pass it the argument `--joshua-args "list of
+ joshua args"`. These will then be passed to the decoder when it is
+ invoked. You can enable your feature functions, then using
+ something like
+
+ $JOSHUA/bin/pipeline.pl --joshua-args '-feature-function OracleFeature'
+
+ If you call the decoder directly, you can just put that line in
+ the configuration file, e.g.,
+
+ feature-function = OracleFeature
+
+ or you can pass it directly to Joshua on the command line using
+ the standard notation, e.g.,
+
+ $JOSHUA/bin/joshua-decoder -feature-function OracleFeature
+
+ These could be stacked, e.g.,
+
+ $JOSHUA/bin/joshua-decoder -feature-function OracleFeature \
+ -feature-function MagicFeature \
+ -feature-function MTSolverFeature \
+ ...
+
+
