diff --git a/speechcommands/README.md b/speechcommands/README.md
index 79bbb9b4..07002594 100644
--- a/speechcommands/README.md
+++ b/speechcommands/README.md
@@ -8,10 +8,6 @@ dataset.
 
 ## Pre-requisites
 
-Follow the [installation
-instructions](https://ml-explore.github.io/mlx-data/build/html/install.html)
-for MLX Data.
-
 Install the remaining python requirements:
 
 ```
diff --git a/speechcommands/requirements.txt b/speechcommands/requirements.txt
index 5ca13284..4e6a06dd 100644
--- a/speechcommands/requirements.txt
+++ b/speechcommands/requirements.txt
@@ -1 +1,2 @@
-mlx>=0.0.5
+mlx
+mlx-data
diff --git a/whisper/README.md b/whisper/README.md
index e785d9bb..847d5b8b 100644
--- a/whisper/README.md
+++ b/whisper/README.md
@@ -52,13 +52,13 @@ import whisper
 text = whisper.transcribe(speech_file)["text"]
 ```
 
-Choose the model by setting `hf_path_or_repo`. For example:
+Choose the model by setting `path_or_hf_repo`. For example:
 
 ```python
-result = whisper.transcribe(speech_file, hf_path_or_repo="models/large")
+result = whisper.transcribe(speech_file, path_or_hf_repo="models/large")
 ```
 
-This will load the model contained in `models/large`. The `hf_path_or_repo`
+This will load the model contained in `models/large`. The `path_or_hf_repo`
 can also point to an MLX-style Whisper model on the Hugging Face Hub. In this
 case, the model will be automatically downloaded.