docs: document new load from hf and save

explodinggradients · Oct 14, 2024 · 4b5120a · 4b5120a
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diff --git a/docs/getstarted/rag_evaluation.md b/docs/getstarted/rag_evaluation.md
@@ -16,16 +16,7 @@ Converting data to ragas [evaluation dataset](../concepts/components/eval_datase
 ```python
 from ragas import EvaluationDataset, SingleTurnSample
 
-samples = []
-for row in dataset['eval']:
-    sample = SingleTurnSample(
-        user_input=row['user_input'],
-        reference=row['reference'],
-        response=row['response'],
-        retrieved_contexts=row['retrieved_contexts']
-    )
-    samples.append(sample)
-eval_dataset = EvaluationDataset(samples=samples)
+eval_dataset = EvaluationDataset.from_hf_dataset(dataset["eval"])
 ```
 
 

diff --git a/docs/howtos/migrations/migrate_from_v01_to_v02.md b/docs/howtos/migrations/migrate_from_v01_to_v02.md
@@ -19,22 +19,13 @@ You can easily translate
 from ragas import EvaluationDataset, SingleTurnSample
 
 hf_dataset = ... # your huggingface evaluation dataset
-samples = []
-for row in hf_dataset:
-    sample = SingleTurnSample(
-        user_input=row['user_input'],
-        reference=row['reference'],
-        response=row['response'],
-        retrieved_contexts=row['retrieved_contexts']
-    )
-    samples.append(sample)
-eval_dataset = EvaluationDataset(samples=samples)
+eval_dataset = EvaluationDataset.from_hf_dataset(hf_dataset)
 
 # save eval dataset
-TODO
+eval_dataset.to_csv("path/to/save/dataset.csv")
 
 # load eva dataset
-TODO
+eval_dataset = EvaluationDataset.from_csv("path/to/save/dataset.csv")
 ```
 
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