add correct usage in huggingface

README.md

@@ -89,20 +89,16 @@ This project fine‑tunes a Wav2Vec2 audio classifier (e.g., `facebook/wav2vec2-
 
 Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Evaluate on target devices/microphones; add noise augmentation and tune detection thresholds for deployment context.
 
-## How to use it in HuggingFace
+## Usage in HuggingFace (Recommended)
 ```bash
 from transformers import AutoFeatureExtractor, AutoModelForAudioClassification, pipeline
 
 model_id = "Amirhossein75/Keyword-Spotting"
-```
 # Option A — simple:
-```bash
 clf = pipeline("audio-classification", model=model_id)
 print(clf("path/to/1sec_16kHz.wav"))
-```
 
 # Option B — manual pre/post:
-```bash
 fe = AutoFeatureExtractor.from_pretrained(model_id)
 model = AutoModelForAudioClassification.from_pretrained(model_id)
 
@@ -115,6 +111,7 @@ pred_id = int(logits.argmax(-1))
 print(model.config.id2label[pred_id])
 
 ```
+**Note** : it is better not to use the `AutoProcessor`
 
 ## How to Get Started with the Model
 

vocab.json

@@ -0,0 +1 @@
+{"<pad>": 0, "<s>": 1, "</s>": 2, "<unk>": 3, "|": 4, "E": 5, "T": 6, "A": 7, "O": 8, "N": 9, "I": 10, "H": 11, "S": 12, "R": 13, "D": 14, "L": 15, "U": 16, "M": 17, "W": 18, "C": 19, "F": 20, "G": 21, "Y": 22, "P": 23, "B": 24, "V": 25, "K": 26, "'": 27, "X": 28, "J": 29, "Q": 30, "Z": 31}