Tweaks to the model card

README.md

@@ -36,49 +36,23 @@ NatureLM-audio is an audio-language model designed to address bioacoustic tasks
 ### Direct Use
 
 NatureLM-audio can be used directly for bioacoustic tasks such as species classification, detection, and captioning. It is particularly useful for biodiversity monitoring, conservation, and animal behavior studies.
-```python
-from NatureLM.models import NatureLM
-
-# Download the model from HuggingFace
-model = NatureLM.from_pretrained("EarthSpeciesProject/NatureLM-audio")
-model = model.eval().to("cuda")
-```
-
-```python
-from NatureLM.infer import Pipeline
-
-# pass your audio files in as file paths or as numpy arrays
-# NOTE: the Pipeline class will automatically load the audio and convert them to numpy arrays
-audio_paths = ["assets/nri-GreenTreeFrogEvergladesNP.mp3"]  # wav, mp3, ogg, flac are supported.
-
-# Create a list of queries. You may also pass a single query as a string for multiple audios.
-# The same query will be used for all audios.
-queries = ["What is the common name for the focal species in the audio? Answer:"]
-
-pipeline = Pipeline(model=model)
-# NOTE: you can also just do pipeline = Pipeline() which will download the model automatically
-
-# Run the model over the audio in sliding windows of 10 seconds with a hop length of 10 seconds
-results = pipeline(audio_paths, queries, window_length_seconds=10.0, hop_length_seconds=10.0)
-print(results)
-# ['#0.00s - 10.00s#: Green Treefrog\n']
-```
 
 Example prompts:
 
-Prompt: What is the common name for the focal species in the audio? 
-Answer: Humpback Whale
+Prompt: What is the common name for the focal species in the audio?   
+Answer: Humpback Whale 
 
-Prompt: Which of these, if any, are present in the audio recording? Single pulse gibbon call, Multiple pulse gibbon call, Gibbon duet, None. 
+Prompt: Which of these, if any, are present in the audio recording? Single pulse gibbon call, Multiple pulse gibbon call, Gibbon duet, None.   
 Answer: Gibbon duet
 
-Prompt: What is the common name for the focal species in the audio? 
+Prompt: What is the common name for the focal species in the audio?   
 Answer: Spectacled Tetraka
 
-Prompt: What is the life stage of the focal species in the audio? 
+Prompt: What is the life stage of the focal species in the audio?   
 Answer: Juvenile 
 
-Prompt: What type of vocalization is heard from the focal species in the audio? Answer with either 'call' or 'song'.
+Prompt: What type of vocalization is heard from the focal species in the audio?   
+Answer with either 'call' or 'song'.
 
 Prompt: Caption the audio, using the common name for any animal species.
 
@@ -103,7 +77,34 @@ Users should be aware of the risks, biases, and limitations of the model. It is
 
 ## How to Get Started with the Model
 
-Refer to the GitHub [repository](https://github.com/earthspecies/naturelm-audio) for examples of model usage.
+Instantiating the model:
+
+```python
+from NatureLM.models import NatureLM
+
+# Download the model from HuggingFace
+model = NatureLM.from_pretrained("EarthSpeciesProject/NatureLM-audio")
+model = model.eval().to("cuda")
+```
+
+Using the model:
+
+```python
+from NatureLM.infer import Pipeline
+
+audio_paths = ["assets/nri-GreenTreeFrogEvergladesNP.mp3"]  
+queries = ["What is the common name for the focal species in the audio? Answer:"]
+
+pipeline = Pipeline(model=model)
+
+# Run the model over the audio in sliding windows of 10 seconds with a hop length of 10 seconds
+results = pipeline(audio_paths, queries, window_length_seconds=10.0, hop_length_seconds=10.0)
+
+print(results)
+# ['#0.00s - 10.00s#: Green Treefrog\n']
+```
+
+Refer to the GitHub [repository](https://github.com/earthspecies/naturelm-audio) for more details.
 
 ## Training Details