diff --git a/Makefile b/Makefile
index 5c4214f9..ebdb50ba 100644
--- a/Makefile
+++ b/Makefile
@@ -378,3 +378,22 @@ train-and-start-bt-jobs: ${WORKDIR}/${MODEL}.${MODELTYPE}.model${NR}.done
 	${MAKE} local-dist
 	${MAKE} -C backtranslate MODELHOME=${MODELDIR} translate-all-wikis-jobs
 
+
+ALL_RELEASED_MODELS = ${wildcard models-tatoeba/*/*.zip}
+ALL_VOCABS_FIXED = ${patsubst %.zip,%.fixed-vocab,${ALL_RELEASED_MODELS}}
+
+fix-released-vocabs: ${ALL_VOCABS_FIXED}
+
+%.fixed-vocab: %.zip
+	@( v=`unzip -l $<  | grep 'vocab.yml$$' | sed 's/^.* //'`; \
+	  if [ "$$v" != "" ]; then \
+	    unzip $< $$v; \
+	    python3 scripts/fix_vocab.py $$v; \
+	    if [ -e $$v.bak ]; then \
+	      echo "update $$v in $<"; \
+	      zip $< $$v $$v.bak; \
+	    else \
+	      echo "vocab $$v is fine in $<"; \
+	    fi; \
+	    rm -f $$v $$v.bak; \
+	  fi )
diff --git a/lib/allas.mk b/lib/allas.mk
index 8b912b21..b28a377a 100644
--- a/lib/allas.mk
+++ b/lib/allas.mk
@@ -20,6 +20,9 @@ WORK_DESTDIR      ?= ${WORKHOME}
 WORK_CONTAINER    ?= OPUS-MT-train_${notdir ${WORKHOME}}-${WHOAMI}
 WORK_CONTAINER_JT ?= OPUS-MT-train_${notdir ${WORKHOME}}-tiedeman
 
+ALLAS_STORAGE_URL = https://object.pouta.csc.fi/
+
+
 ## store workdir on allas
 store:
 	cd ${WORK_SRCDIR} && a-put -b ${WORK_CONTAINER} --nc --follow-links --override ${LANGPAIRSTR}
@@ -43,3 +46,41 @@ fetch-data:
 	mkdir -p ${WORK_DESTDIR}
 	cd ${WORK_DESTDIR} && a-get ${WORK_CONTAINER}/data.tar
 
+
+
+## generic recipe for storing work data and removing it from the file system
+## DANGEROUS --- this really deletes the data!
+## NOTE: makes container also world-readable (see swift post command)
+##       --> this makes it easier to fetch things without login credentials
+##       --> should not store sensitive data here!
+%.stored: %
+	if [ "$(firstword $(subst -, ,$(subst /, ,$@)))" == "work" ]; then \
+	  b=OPUS-MT-train_$(subst /,-,$(dir $@))${WHOAMI}; \
+	  cd $(dir $@); \
+	  a-put -b $$b --nc --follow-links --override $(notdir $<); \
+	  rm -fr $(notdir $<); \
+	  touch $(notdir $@); \
+	  rm -f $(notdir $(@:stored=.fetched)); \
+	  swift post $$b --read-acl ".r:*"
+	fi
+
+
+## TODO: fetch with wget instead of using a-commands
+## fetch work data from allas
+%.fetched:
+	if [ "$(firstword $(subst -, ,$(subst /, ,$@)))" == "work" ]; then \
+	  cd $(dir $@); \
+	  a-get OPUS-MT-train_$(subst /,-,$(dir $@))${WHOAMI}/$(notdir $(@:.fetched=.tar)); \
+	  touch $(notdir $@); \
+	  rm -f $(notdir $(@:fetched=.stored)); \
+	fi
+
+## another way of fetching work data
+## requires settings SRCLANGS and TRGLANGS (or LANGPAIRSTR directly)
+work-%/${LANGPAIRSTR}:
+	mkdir -p $(dir $@)
+	cd $(dir $@) && a-get OPUS-MT-train_$(subst /,-,$(dir $@))${WHOAMI}/${LANGPAIRSTR}.tar
+
+
+UPLOAD_MODELS=$(patsubst %,%.stored,${wildcard work-tatoeba/[dg-rt-z]*})
+upload-workfiles: ${UPLOAD_MODELS}
diff --git a/lib/config.mk b/lib/config.mk
index 1befd5da..9eb54686 100644
--- a/lib/config.mk
+++ b/lib/config.mk
@@ -281,8 +281,6 @@ TUNE_GPUJOB_SUBMIT  ?=
 
 
 
-
-
 ## existing projects in WORKHOME
 ALL_LANG_PAIRS := ${shell ls ${WORKHOME} | grep -- '-' | grep -v old}
 ALL_BILINGUAL_MODELS := ${shell echo '${ALL_LANG_PAIRS}' | tr ' ' "\n" |  grep -v -- '\+'}
@@ -293,6 +291,8 @@ ALL_MULTILINGUAL_MODELS := ${shell echo '${ALL_LANG_PAIRS}' | tr ' ' "\n" | grep
 ## pre-processing and vocabulary
 ##----------------------------------------------------------------------------
 
+## type of subword segmentation (bpe|spm)
+## model size (NOTE: BPESIZE is also used for sentencepiece!)
 SUBWORDS   ?= spm
 BPESIZE    ?= 32000
 SRCBPESIZE ?= ${BPESIZE}
@@ -306,10 +306,12 @@ BPETRGMODEL  ?= ${WORKDIR}/train/${BPEMODELNAME}.trg.bpe${TRGBPESIZE:000=}k-mode
 SPMSRCMODEL  ?= ${WORKDIR}/train/${BPEMODELNAME}.src.spm${SRCBPESIZE:000=}k-model
 SPMTRGMODEL  ?= ${WORKDIR}/train/${BPEMODELNAME}.trg.spm${TRGBPESIZE:000=}k-model
 
+## don't delete BPE/sentencepiece models!
 .PRECIOUS: ${BPESRCMODEL} ${BPETRGMODEL}
 .PRECIOUS: ${SPMSRCMODEL} ${SPMTRGMODEL}
 
-
+## size of the joined vocabulary
+## TODO: heuristically add 1,000 to cover language labels is a bit ad-hoc
 VOCABSIZE  ?= $$((${SRCBPESIZE} + ${TRGBPESIZE} + 1000))
 
 ## for document-level models
@@ -353,7 +355,7 @@ WORKDIR  = ${WORKHOME}/${LANGPAIRSTR}
 MODELDIR = ${WORKHOME}/models/${LANGPAIRSTR}
 SPMDIR   = ${WORKHOME}/SentencePieceModels
 
-## data sets
+## train data sets (word alignment for the guided alignment option)
 TRAIN_BASE = ${WORKDIR}/train/${DATASET}
 TRAIN_SRC  = ${TRAIN_BASE}.src
 TRAIN_TRG  = ${TRAIN_BASE}.trg
@@ -364,7 +366,7 @@ LOCAL_TRAIN_SRC = ${TMPDIR}/${LANGPAIRSTR}/train/${DATASET}.src
 LOCAL_TRAIN_TRG = ${TMPDIR}/${LANGPAIRSTR}/train/${DATASET}.trg
 LOCAL_MONO_DATA = ${TMPDIR}/${LANGSTR}/train/${DATASET}.mono
 
-
+## dev and test data
 DEV_SRC   ?= ${WORKDIR}/val/${DEVSET_NAME}.src
 DEV_TRG   ?= ${WORKDIR}/val/${DEVSET_NAME}.trg
 
@@ -372,8 +374,15 @@ TEST_SRC  ?= ${WORKDIR}/test/${TESTSET_NAME}.src
 TEST_TRG  ?= ${WORKDIR}/test/${TESTSET_NAME}.trg
 
 
+## model basename and optional sub-dir
+
 MODEL_SUBDIR =
 MODEL        =  ${MODEL_SUBDIR}${DATASET}${TRAINSIZE}.${PRE_SRC}-${PRE_TRG}
+
+
+## supported model types
+## configuration for each type is in lib/train.mk
+
 MODELTYPES   = 	transformer \
 		transformer-big \
 		transformer-align \
diff --git a/lib/generic.mk b/lib/generic.mk
index b3d6a5df..060af28c 100644
--- a/lib/generic.mk
+++ b/lib/generic.mk
@@ -372,6 +372,12 @@ endif
 	${@:-pivot=}
 
 
+%-big-align:
+	${MAKE} PRE_TRAINED_MODEL=${MODEL_FINAL} \
+		MODELTYPE=transformer-big-align \
+	${@:-big-align=}
+
+
 
 
 ## run a multigpu job (2 or 4 GPUs)
diff --git a/lib/projects/distill.mk b/lib/projects/distill.mk
index c81ceaea..05434fbf 100644
--- a/lib/projects/distill.mk
+++ b/lib/projects/distill.mk
@@ -74,6 +74,37 @@ afreng-bt-tiny:
 
 
 
+afreng:
+	make 	TATOEBA_VERSION=v2020-07-28 \
+		SRCLANGS=afr TRGLANGS=eng \
+	all-job-tatoeba
+
+
+afreng-small:
+	make 	TATOEBA_VERSION=v2020-07-28 \
+		BT_CONTINUE_EXISTING=0 \
+		SRCLANGS=afr TRGLANGS=eng \
+		MODELTYPE=transformer-small-align \
+		MARIAN_WORKSPACE=10000 \
+	all-job-tatoeba
+
+afreng-tiny:
+	make 	TATOEBA_VERSION=v2020-07-28 \
+		BT_CONTINUE_EXISTING=0 \
+		SRCLANGS=afr TRGLANGS=eng \
+		MODELTYPE=transformer-tiny-align \
+		MARIAN_WORKSPACE=10000 \
+	all-job-tatoeba
+
+afreng-small-eval:
+	make 	TATOEBA_VERSION=v2020-07-28 \
+		BT_CONTINUE_EXISTING=0 \
+		SRCLANGS=afr TRGLANGS=eng \
+		MODELTYPE=transformer-small-align \
+		MARIAN_WORKSPACE=10000 \
+	eval-tatoeba
+
+
 
 
 
diff --git a/lib/train.mk b/lib/train.mk
index 9ebb0ed4..7823db2f 100644
--- a/lib/train.mk
+++ b/lib/train.mk
@@ -6,35 +6,26 @@
 #------------------------------------------------------------------------
 
 
+
+## extract vocabulary from sentence piece model
+
+${WORKDIR}/${MODEL}.src.vocab: ${SPMSRCMODEL}
+	cut -f1 < $<.vocab > $@
+ifeq (${USE_TARGET_LABELS},1)
+	echo "${TARGET_LABELS}" | tr ' ' "\n" >> $@
+endif
+
+${WORKDIR}/${MODEL}.trg.vocab: ${SPMTRGMODEL}
+	cut -f1 < $<.vocab > $@
+
+
 ifeq (${SUBWORDS},spm)
 
 ## make vocabulary from the source and target language specific
 ## sentence piece models (concatenate and yamlify)
-## TODO: verify that this becomes valid YAML!
 
-${MODEL_VOCAB}: ${SPMSRCMODEL} ${SPMTRGMODEL}
-ifneq (${MODEL_LATEST_VOCAB},)
-ifneq (${MODEL_LATEST_VOCAB},${MODEL_VOCAB})
-	cp ${MODEL_LATEST_VOCAB} ${MODEL_VOCAB}
-endif
-else
-	cut -f1 < ${word 1,$^}.vocab > ${@:.vocab.yml=.src.vocab}
-	cut -f1 < ${word 2,$^}.vocab > ${@:.vocab.yml=.trg.vocab}
-ifeq (${USE_TARGET_LABELS},1)
-	echo "${TARGET_LABELS}" | tr ' ' "\n" >> ${@:.vocab.yml=.src.vocab}
-endif
-	cat ${@:.vocab.yml=.src.vocab} ${@:.vocab.yml=.trg.vocab} | \
-	sort -u | scripts/vocab2yaml.py > $@
-
-## old buggy style ...
-#	cat ${@:.vocab.yml=.src.vocab} ${@:.vocab.yml=.trg.vocab} | \
-#	sort -u | nl -v 0 | sed 's/^ *//'> $@.numbered
-#	cut -f1 $@.numbered > $@.ids
-#	cut -f2 $@.numbered | sed 's/\\/\\\\/g;s/\"/\\\"/g;s/^\(.*\)$$/"\1"/;s/$$/:/'> $@.tokens
-#	paste -d ' ' $@.tokens $@.ids > $@
-#	rm -f $@.tokens $@.ids $@.numbered
-
-endif
+${WORKDIR}/${MODEL}.vocab.yml: ${WORKDIR}/${MODEL}.src.vocab ${WORKDIR}/${MODEL}.trg.vocab
+	cat $^ | sort -u | scripts/vocab2yaml.py > $@
 
 else
 
@@ -42,12 +33,12 @@ else
 ## - no new vocabulary is created if the file already exists!
 ## - need to delete the file if you want to create a new one!
 
-${MODEL_VOCAB}:	${TRAIN_SRC}.clean.${PRE_SRC}${TRAINSIZE}.gz \
-		${TRAIN_TRG}.clean.${PRE_TRG}${TRAINSIZE}.gz
-ifeq ($(wildcard ${MODEL_SRCVOCAB} ${MODEL_TRGVOCAB}),)
-ifneq (${MODEL_LATEST_VOCAB},)
-ifneq (${MODEL_LATEST_VOCAB},${MODEL_VOCAB})
-	cp ${MODEL_LATEST_VOCAB} ${MODEL_VOCAB}
+${WORKDIR}/${MODEL}.vocab.yml:	${TRAIN_SRC}.clean.${PRE_SRC}${TRAINSIZE}.gz \
+				${TRAIN_TRG}.clean.${PRE_TRG}${TRAINSIZE}.gz
+ifeq ($(wildcard $@),)
+ifneq ($(wildcard ${MODEL_LATEST_VOCAB}),)
+ifneq (${MODEL_LATEST_VOCAB},$@)
+	cp ${MODEL_LATEST_VOCAB} $@
 endif
 else
 	mkdir -p ${dir $@}
@@ -59,35 +50,12 @@ else
 	@echo "WARNING! Delete the file if you want to start from scratch!"
 	touch $@
 endif
-
 endif
 
 
-
-## if USE_SPM_VOCAB is set:
-## get separate source and target language vocabularies
-## from the two individual sentence piece models
-
-ifeq ($(USE_SPM_VOCAB),1)
-${MODEL_SRCVOCAB}: ${SPMSRCMODEL}
-	cut -f1 < $<.vocab > $@
-ifeq (${USE_TARGET_LABELS},1)
-	echo "${TARGET_LABELS}" | tr ' ' "\n" >> $@
-endif
-
-${MODEL_TRGVOCAB}: ${SPMTRGMODEL}
-	cut -f1  < $<.vocab > $@
-endif
-
-
-
-
 print-latest:
-ifneq (${wildcard ${MODEL_LATEST}},)
-ifeq (${wildcard ${MODEL_START}},)
-	@echo "cp ${MODEL_LATEST} ${MODEL_START}"
-endif
-endif
+	@echo "latest model: ${MODEL_LATEST}"
+	@echo "start model:  ${MODEL_START}"
 
 
 
@@ -100,15 +68,12 @@ endif
 MARIAN_MODELS_DONE   = 	${patsubst %,${WORKDIR}/${MODEL}.%.model${NR}.done,${MODELTYPES}}
 
 MARIAN_TRAIN_PREREQS = 	${TRAIN_SRC}.clean.${PRE_SRC}${TRAINSIZE}.gz \
-			${TRAIN_TRG}.clean.${PRE_TRG}${TRAINSIZE}.gz
+			${TRAIN_TRG}.clean.${PRE_TRG}${TRAINSIZE}.gz \
+			$(sort ${MODEL_SRCVOCAB} ${MODEL_TRGVOCAB})
 
 
 ## define validation and early-stopping parameters
 ## as well as pre-requisites for training the model
-##
-## NEW: take away dependency on ${MODEL_VOCAB}
-## (will be created by marian if it does not exist)
-## TODO: should we create the dependency again?
 
 ifndef SKIP_VALIDATION
   MARIAN_TRAIN_PREREQS += ${DEV_SRC}.${PRE_SRC} ${DEV_TRG}.${PRE_TRG}
@@ -137,9 +102,15 @@ else
 endif
 
 
+# start weights with a pre-trained model
+
+ifneq (${wildcard ${PRE_TRAINED_MODEL}},)
+  MARIAN_EXTRA += --pretrained-model ${PRE_TRAINED_MODEL}
+endif
+
 
 ## dependencies and extra parameters
-## for models with guided alignment
+## for different models and guided alignment
 
 ifeq (${MODELTYPE},transformer-align)
   MARIAN_TRAIN_PREREQS += ${TRAIN_ALG}
@@ -176,7 +147,6 @@ endif
 ifeq (${MODELTYPE},transformer-big-align)
   MARIAN_ENC_DEPTH = 12
   MARIAN_ATT_HEADS = 16
-  MARIAN_DIM_EMB = 1024
   MARIAN_TRAIN_PREREQS += ${TRAIN_ALG}
   MARIAN_EXTRA += --guided-alignment ${TRAIN_ALG}
   GPUJOB_HPC_MEM = 16g
@@ -185,10 +155,10 @@ endif
 ifeq (${MODELTYPE},transformer-big)
   MARIAN_ENC_DEPTH = 12
   MARIAN_ATT_HEADS = 16
-  MARIAN_DIM_EMB = 1024
   GPUJOB_HPC_MEM = 16g
 endif
 
+#  MARIAN_DIM_EMB = 1024
 
 
 ## finally: recipe for training transformer model
@@ -200,19 +170,13 @@ ${MARIAN_MODELS_DONE}: ${MARIAN_TRAIN_PREREQS}
 ## (check lib/config.mk to see how the latest model is found)
 ##--------------------------------------------------------------------
 ifeq (${wildcard ${MODEL_START}},)
-ifneq (${MODEL_LATEST},)
-ifneq (${MODEL_LATEST_VOCAB},)
-ifneq (${MODEL_LATEST_VOCAB},${MODEL_VOCAB})
-	cp ${MODEL_LATEST_VOCAB} ${MODEL_VOCAB}
-endif
+ifneq (${wildcard ${MODEL_LATEST}},)
 ifneq (${MODEL_LATEST},${MODEL_START})
 	cp ${MODEL_LATEST} ${MODEL_START}
 endif
 endif
 endif
-endif
 ##--------------------------------------------------------------------
-	${MAKE} ${MODEL_SRCVOCAB} ${MODEL_TRGVOCAB}
 	${LOADMODS} && ${MARIAN_TRAIN} ${MARIAN_EXTRA} \
 	${MARIAN_STOP_CRITERIA} \
         --model $(@:.done=.npz) \
diff --git a/scripts/fix_vocab.py b/scripts/fix_vocab.py
index c6965880..5e34d0fb 100755
--- a/scripts/fix_vocab.py
+++ b/scripts/fix_vocab.py
@@ -10,7 +10,7 @@ filename = sys.argv[1]
 
 try:
     input = open(filename, 'r')
-    yaml.load(input)
+    yaml.safe_load(input)
 except:
     print('YAML file is broken - try to fix it!')
     print(f'copy {filename} to {filename}.bak')