fix financial phrase bank dataset links

holgerroth · holgerroth · commit 8b867224f4ec · 2025-07-03T19:15:56.000-04:00
diff --git a/integration/nemo/examples/peft/peft.ipynb b/integration/nemo/examples/peft/peft.ipynb
@@ -70,7 +70,7 @@
    "metadata": {},
    "source": [
     "## Data preprocessing\n",
-    "As our downstream task, we will use the [Financial PhraseBank dataset](https://huggingface.co/datasets/financial_phrasebank) for sentiment analysis.\n",
+    "As our downstream task, we will use the [Financial PhraseBank dataset](https://www.researchgate.net/publication/251231364_FinancialPhraseBank-v10) for sentiment analysis.\n",
     "\n",
     "The Financial PhraseBank dataset contains the sentiments for financial news headlines from a retail investor's perspective. Further details about the dataset can be found in Malo et al.'s [\"Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts\"](https://arxiv.org/abs/1307.5336).\n",
     "\n",
diff --git a/integration/nemo/examples/prompt_learning/prompt_learning.ipynb b/integration/nemo/examples/prompt_learning/prompt_learning.ipynb
@@ -76,7 +76,7 @@
    "metadata": {},
    "source": [
     "## Data preprocessing\n",
-    "As our downstream task, we will use the [Financial PhraseBank dataset](https://huggingface.co/datasets/financial_phrasebank) for sentiment analysis.\n",
+    "As our downstream task, we will use the [Financial PhraseBank dataset](https://www.researchgate.net/publication/251231364_FinancialPhraseBank-v10) for sentiment analysis.\n",
     "\n",
     "The Financial PhraseBank dataset contains the sentiments for financial news headlines from a retail investor's perspective. Further details about the dataset can be found in Malo et al.'s [\"Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts\"](https://arxiv.org/abs/1307.5336).\n"
    ]
diff --git a/integration/nemo/examples/prompt_learning/prompt_learning_20B.md b/integration/nemo/examples/prompt_learning/prompt_learning_20B.md
@@ -58,7 +58,7 @@ python3 megatron_change_num_partitions.py --model_file ${source_ckpt} --target_f
 ```
 
 ## Data preprocessing
-As our downstream task, we will use the [Financial PhraseBank dataset](https://huggingface.co/datasets/financial_phrasebank) for sentiment analysis.
+As our downstream task, we will use the [Financial PhraseBank dataset](https://www.researchgate.net/publication/251231364_FinancialPhraseBank-v10) for sentiment analysis.
 
 The Financial PhraseBank dataset contains the sentiments for financial news headlines from a retail investor's perspective. 
 Further details about the dataset can be found in Malo et al.'s ["Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts"](https://arxiv.org/abs/1307.5336).

Original file line number	Diff line number	Diff line change
`@@ -76,7 +76,7 @@`
`76`	`76`	`"metadata": {},`
`77`	`77`	`"source": [`
`78`	`78`	`"## Data preprocessing\n",`
`79`		`- "As our downstream task, we will use the [Financial PhraseBank dataset](https://huggingface.co/datasets/financial_phrasebank) for sentiment analysis.\n",`
	`79`	`+ "As our downstream task, we will use the [Financial PhraseBank dataset](https://www.researchgate.net/publication/251231364_FinancialPhraseBank-v10) for sentiment analysis.\n",`
`80`	`80`	`"\n",`
`81`	`81`	`"The Financial PhraseBank dataset contains the sentiments for financial news headlines from a retail investor's perspective. Further details about the dataset can be found in Malo et al.'s [\"Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts\"](https://arxiv.org/abs/1307.5336).\n"`
`82`	`82`	`]`