diff --git a/dev-0/out.tsv b/dev-0/out.tsv
new file mode 100644
index 0000000..c8b523e
--- /dev/null
+++ b/dev-0/out.tsv
@@ -0,0 +1,87 @@
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\ No newline at end of file
diff --git a/geval b/geval
new file mode 100755
index 0000000..b68b316
Binary files /dev/null and b/geval differ
diff --git a/prog.py b/prog.py
index 0a10276..3843b76 100644
--- a/prog.py
+++ b/prog.py
@@ -3,11 +3,14 @@ import numpy as np
 import sklearn.metrics
 from sklearn.cluster import KMeans
 
-with open("dev-0/in.tsv") as f:
+with open("test-A/in.tsv") as f:
     content = f.readlines()
     vectorizer = TfidfVectorizer(ngram_range=(1,2), use_idf = False)
     vectorizer = TfidfVectorizer()
     document_vectors = vectorizer.fit_transform(content)
-    kmeans = KMeans(n_clusters=4, random_state=0).fit(document_vectors)
+    kmeans = KMeans(n_clusters=77, random_state=0).fit(document_vectors)
     pred_y = kmeans.fit_predict(document_vectors)
-    print(pred_y)
+    t=kmeans.labels_
+    t=np.array2string(t, precision=2, separator='\n',suppress_small=True)
+    f = open("test-A/out.tsv", "a")
+    f.write(t)
diff --git a/test-A/out.tsv b/test-A/out.tsv
new file mode 100644
index 0000000..214a99c
--- /dev/null
+++ b/test-A/out.tsv
@@ -0,0 +1,691 @@
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\ No newline at end of file