diff --git a/common b/common
index 62268aab..b60eda08 160000
--- a/common
+++ b/common
@@ -1 +1 @@
-Subproject commit 62268aab3ea7aeac754a9b134755b83d18e43975
+Subproject commit b60eda085e9cd505ec169fa30cc7e919e8563ad2
diff --git a/src/methods/geneformer/config.vsh.yaml b/src/methods/geneformer/config.vsh.yaml
index 6be7998c..a98ab008 100644
--- a/src/methods/geneformer/config.vsh.yaml
+++ b/src/methods/geneformer/config.vsh.yaml
@@ -21,20 +21,24 @@ info:
   method_types: [embedding]
   variants:
     geneformer_12L_95M_i4096:
-      model: "gf-12L-95M-i4096"
+      model: gf-12L-95M-i4096
     geneformer_6L_30M_i2048:
-      model: "gf-6L-30M-i2048"
+      model: gf-6L-30M-i2048
     geneformer_12L_30M_i2048:
-      model: "gf-12L-30M-i2048"
+      model: gf-12L-30M-i2048
     geneformer_20L_95M_i4096:
-      model: "gf-20L-95M-i4096"
+      model: gf-20L-95M-i4096
 
 arguments:
-  - name: "--model"
-    type: "string"
+  - name: --model
+    type: string
     description: String representing the Geneformer model to use
-    choices: ["gf-6L-30M-i2048", "gf-12L-30M-i2048", "gf-12L-95M-i4096", "gf-20L-95M-i4096"]
-    default: "gf-12L-95M-i4096"
+    choices:
+      - gf-6L-30M-i2048
+      - gf-12L-30M-i2048
+      - gf-12L-95M-i4096
+      - gf-20L-95M-i4096
+    default: gf-12L-95M-i4096
 
 resources:
   - type: python_script
@@ -48,9 +52,9 @@ engines:
     setup:
       - type: python
         pip:
-        - pyarrow<15.0.0a0,>=14.0.1
-        - huggingface_hub
-        - git+https://huggingface.co/ctheodoris/Geneformer.git
+          - pyarrow<15.0.0a0,>=14.0.1
+          - huggingface_hub
+          - git+https://huggingface.co/ctheodoris/Geneformer.git
 
 runners:
   - type: executable
diff --git a/src/methods/geneformer/script.py b/src/methods/geneformer/script.py
index 521b8f5c..902a7735 100644
--- a/src/methods/geneformer/script.py
+++ b/src/methods/geneformer/script.py
@@ -23,22 +23,24 @@
 
 print(">>> Reading input...", flush=True)
 sys.path.append(meta["resources_dir"])
-from read_anndata_partial import read_anndata
 from exit_codes import exit_non_applicable
+from read_anndata_partial import read_anndata
 
 adata = read_anndata(par["input"], X="layers/counts", obs="obs", var="var", uns="uns")
 
 if adata.uns["dataset_organism"] != "homo_sapiens":
     exit_non_applicable(
         f"Geneformer can only be used with human data "
-        f"(dataset_organism == \"{adata.uns['dataset_organism']}\")"
+        f'(dataset_organism == "{adata.uns["dataset_organism"]}")'
     )
 
 # Set adata.var_names to gene IDs
 adata.var_names = adata.var["feature_id"]
 is_ensembl = all(var_name.startswith("ENSG") for var_name in adata.var_names)
 if not is_ensembl:
-    raise ValueError(f"Geneformer requires adata.var_names to contain ENSEMBL gene ids")
+    exit_non_applicable(
+        "Geneformer requires adata.var_names to contain ENSEMBL gene ids"
+    )
 
 print(f">>> Getting settings for model '{par['model']}'...", flush=True)
 model_split = par["model"].split("-")
@@ -97,18 +99,42 @@
 adata.write_h5ad(os.path.join(input_dir, "input.h5ad"))
 print(adata)
 
+
+# Function to try parallel execution and fall batch to a single processor if it fails
+def tryParallelFunction(fun, label):
+    try:
+        fun(nproc=n_processors)
+    except RuntimeError as e:
+        # Retry with nproc=1 if error message contains "One of the subprocesses has abruptly died"
+        if "subprocess" in str(e) and "died" in str(e):
+            print(f"{label} failed. Error message: {e}", flush=True)
+            print("Retrying with nproc=1", flush=True)
+            fun(nproc=1)
+        else:
+            raise e
+
+
 print(">>> Tokenizing data...", flush=True)
 special_token = model_details["dataset"] == "95M"
 print(f"Input size: {model_details['input_size']}, Special token: {special_token}")
-tokenizer = TranscriptomeTokenizer(
-    nproc=n_processors,
-    model_input_size=model_details["input_size"],
-    special_token=special_token,
-    gene_median_file=dictionary_files["gene_median"],
-    token_dictionary_file=dictionary_files["token"],
-    gene_mapping_file=dictionary_files["ensembl_mapping"],
-)
-tokenizer.tokenize_data(input_dir, tokenized_dir, "tokenized", file_format="h5ad")
+
+
+def tokenize_data(nproc):
+    tokenizer = TranscriptomeTokenizer(
+        nproc=nproc,
+        model_input_size=model_details["input_size"],
+        special_token=special_token,
+        gene_median_file=dictionary_files["gene_median"],
+        token_dictionary_file=dictionary_files["token"],
+        gene_mapping_file=dictionary_files["ensembl_mapping"],
+    )
+
+    tokenizer.tokenize_data(input_dir, tokenized_dir, "tokenized", file_format="h5ad")
+
+    return tokenizer
+
+
+tokenizer = tryParallelFunction(tokenize_data, "Tokenizing data")
 
 print(f">>> Getting model files for model '{par['model']}'...", flush=True)
 model_files = {
diff --git a/src/methods/scgpt_finetuned/config.vsh.yaml b/src/methods/scgpt_finetuned/config.vsh.yaml
index 6b055337..1054e496 100644
--- a/src/methods/scgpt_finetuned/config.vsh.yaml
+++ b/src/methods/scgpt_finetuned/config.vsh.yaml
@@ -44,6 +44,7 @@ resources:
     path: script.py
   - path: /src/utils/read_anndata_partial.py
   - path: scgpt_functions.py
+  - path: /src/utils/exit_codes.py
 
 engines:
   - type: docker
diff --git a/src/methods/scgpt_finetuned/script.py b/src/methods/scgpt_finetuned/script.py
index 7bee08bf..7123bd33 100644
--- a/src/methods/scgpt_finetuned/script.py
+++ b/src/methods/scgpt_finetuned/script.py
@@ -30,6 +30,7 @@
 
 sys.path.append(meta["resources_dir"])
 from read_anndata_partial import read_anndata
+from exit_codes import exit_non_applicable
 from scgpt_functions import evaluate, prepare_data, prepare_dataloader, train
 
 print(f"====== scGPT version {scgpt.__version__} ======", flush=True)
@@ -39,7 +40,7 @@
 adata = read_anndata(par["input"], X="layers/counts", obs="obs", var="var", uns="uns")
 
 if adata.uns["dataset_organism"] != "homo_sapiens":
-    raise ValueError(
+    exit_non_applicable(
         f"scGPT can only be used with human data "
         f"(dataset_organism == \"{adata.uns['dataset_organism']}\")"
     )
diff --git a/src/methods/scprint/config.vsh.yaml b/src/methods/scprint/config.vsh.yaml
index b3ce9d4b..1f2cad83 100644
--- a/src/methods/scprint/config.vsh.yaml
+++ b/src/methods/scprint/config.vsh.yaml
@@ -1,4 +1,4 @@
-__merge__: /src/api/base_method.yaml
+__merge__: /src/api/comp_method.yaml
 
 name: scprint
 label: scPRINT
@@ -38,6 +38,11 @@ info:
       model_name: "medium"
     scprint_small:
       model_name: "small"
+  test_setup:
+    run:
+      model_name: small
+      batch_size: 16
+      max_len: 100
 
 arguments:
   - name: "--model_name"
@@ -49,6 +54,14 @@ arguments:
     type: file
     description: Path to the scPRINT model.
     required: false
+  - name: --batch_size
+    type: integer
+    description: The size of the batches to be used in the DataLoader.
+    default: 64
+  - name: --max_len
+    type: integer
+    description: The maximum length of the gene sequence.
+    default: 4000
 
 resources:
   - type: python_script
@@ -79,4 +92,4 @@ runners:
   - type: executable
   - type: nextflow
     directives:
-      label: [hightime, midmem, midcpu, gpu]
+      label: [hightime, midmem, midcpu, gpu, midsharedmem]
diff --git a/src/methods/scprint/script.py b/src/methods/scprint/script.py
index e76d6f39..5f0c95e8 100644
--- a/src/methods/scprint/script.py
+++ b/src/methods/scprint/script.py
@@ -1,12 +1,13 @@
-import anndata as ad
-from scdataloader import Preprocessor
+import os
 import sys
-from huggingface_hub import hf_hub_download
-from scprint.tasks import Embedder
-from scprint import scPrint
+
+import anndata as ad
 import scprint
 import torch
-import os
+from huggingface_hub import hf_hub_download
+from scdataloader import Preprocessor
+from scprint import scPrint
+from scprint.tasks import Embedder
 
 ## VIASH START
 par = {
@@ -19,8 +20,8 @@
 ## VIASH END
 
 sys.path.append(meta["resources_dir"])
-from read_anndata_partial import read_anndata
 from exit_codes import exit_non_applicable
+from read_anndata_partial import read_anndata
 
 print(f"====== scPRINT version {scprint.__version__} ======", flush=True)
 
@@ -41,7 +42,7 @@
 
 print("\n>>> Preprocessing data...", flush=True)
 preprocessor = Preprocessor(
-    min_valid_genes_id=min(0.9 * adata.n_vars, 10000), # 90% of features up to 10,000
+    min_valid_genes_id=min(0.9 * adata.n_vars, 10000),  # 90% of features up to 10,000
     # Turn off cell filtering to return results for all cells
     filter_cell_by_counts=False,
     min_nnz_genes=False,
@@ -77,7 +78,8 @@
 print(f"Using {n_cores_available} worker cores")
 embedder = Embedder(
     how="random expr",
-    max_len=4000,
+    batch_size=par["batch_size"],
+    max_len=par["max_len"],
     add_zero_genes=0,
     num_workers=n_cores_available,
     doclass=False,
diff --git a/src/metrics/asw_label/config.vsh.yaml b/src/metrics/asw_label/config.vsh.yaml
index 85835857..0392e4e3 100644
--- a/src/metrics/asw_label/config.vsh.yaml
+++ b/src/metrics/asw_label/config.vsh.yaml
@@ -38,4 +38,4 @@ runners:
   - type: executable
   - type: nextflow
     directives:
-      label: [midtime, midmem, lowcpu]
+      label: [hightime, midmem, lowcpu]
diff --git a/src/metrics/isolated_label_asw/config.vsh.yaml b/src/metrics/isolated_label_asw/config.vsh.yaml
index 23b3816b..799aa4ed 100644
--- a/src/metrics/isolated_label_asw/config.vsh.yaml
+++ b/src/metrics/isolated_label_asw/config.vsh.yaml
@@ -39,4 +39,4 @@ runners:
   - type: executable
   - type: nextflow
     directives:
-      label: [midtime, midmem, lowcpu]
+      label: [hightime, midmem, lowcpu]
diff --git a/src/metrics/kbet/config.vsh.yaml b/src/metrics/kbet/config.vsh.yaml
index bbbc6124..8f83724e 100644
--- a/src/metrics/kbet/config.vsh.yaml
+++ b/src/metrics/kbet/config.vsh.yaml
@@ -58,4 +58,4 @@ runners:
   - type: executable
   - type: nextflow
     directives:
-      label: [hightime, highmem, lowcpu]
+      label: [hightime, veryhighmem, lowcpu]
diff --git a/src/metrics/kbet/script.py b/src/metrics/kbet/script.py
index 89bd799e..e5ecc270 100644
--- a/src/metrics/kbet/script.py
+++ b/src/metrics/kbet/script.py
@@ -30,7 +30,7 @@
     type_="embed",
     embed="X_emb",
     scaled=True,
-    verbose=False,
+    verbose=True,
 )
 print(score, flush=True)