Fix more failures

comet-ml · Jul 5, 2024 · 967b56b · 967b56b
1 parent 7f1246a
commit 967b56b
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Showing 3 changed files with 12 additions and 5 deletions.
diff --git a/guides/computer_vision/Computer_Vision_with_Comet.ipynb b/guides/computer_vision/Computer_Vision_with_Comet.ipynb
@@ -131,12 +131,16 @@
     "\n",
     "# Sample 1000 examples from the training split as our training set\n",
     "NUM_TRAIN_SAMPLES = 1000\n",
-    "train_dataset = load_dataset(\"svhn\", \"cropped_digits\", split=\"train\", streaming=True)\n",
+    "train_dataset = load_dataset(\n",
+    "    \"svhn\", \"cropped_digits\", split=\"train\", streaming=True, trust_remote_code=True\n",
+    ")\n",
     "train_dataset = train_dataset.take(NUM_TRAIN_SAMPLES)\n",
     "\n",
     "# Sample 100 examples from the training split as our test set\n",
     "NUM_TEST_SAMPLES = 100\n",
-    "test_dataset = load_dataset(\"svhn\", \"cropped_digits\", split=\"test\", streaming=True)\n",
+    "test_dataset = load_dataset(\n",
+    "    \"svhn\", \"cropped_digits\", split=\"test\", streaming=True, trust_remote_code=True\n",
+    ")\n",
     "test_dataset = test_dataset.take(NUM_TEST_SAMPLES)\n",
     "\n",
     "transforms = T.Compose([T.ToTensor(), T.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])\n",

diff --git a/guides/get-started/Comet_Quickstart.ipynb b/guides/get-started/Comet_Quickstart.ipynb
@@ -76,7 +76,7 @@
    },
    "outputs": [],
    "source": [
-    "%pip install -U comet_ml"
+    "%pip install -U comet_ml \"numpy<2.0.0\""
    ]
   },
   {
@@ -426,7 +426,7 @@
    },
    "outputs": [],
    "source": [
-    "%pip install -U comet_ml torch datasets \"transformers<4.40.0\" scikit-learn accelerate \"numpy<2.0.0\""
+    "%pip install -U comet_ml torch datasets \"transformers<4.40.0\" scikit-learn accelerate"
    ]
   },
   {

diff --git a/...ns/workflow-orchestration/metaflow/metaflow-model-evaluation/metaflow-model-evaluation.py b/...ns/workflow-orchestration/metaflow/metaflow-model-evaluation/metaflow-model-evaluation.py
@@ -178,7 +178,10 @@ def evaluate_classification_metrics(self):
 
         device = "cuda" if torch.cuda.is_available() else "cpu"
         dataset = load_dataset(
-            self.dataset_name, split=self.dataset_split, streaming=True
+            self.dataset_name,
+            split=self.dataset_split,
+            streaming=True,
+            trust_remote_code=True,
         )
         dataset = dataset.shuffle(self.seed, buffer_size=10_000)
         dataset = dataset.take(self.n_samples)