Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- ai4bharat/IndicVoices-ST
+language:
+- hi
+metrics:
+- wer
+base_model:
+- nvidia/stt_en_fastconformer_hybrid_large_streaming_multi
+---
+
+# Model Card for Aibharath-FastConformer-Hindi-ASR
+
+This model is a fine-tuned version of **STT En FastConformer Hybrid Large Streaming** from NVIDIA's NeMo framework, specifically optimized for **Hindi automatic speech recognition (ASR)**. The model has been fine-tuned on the **Aibharath Hindi dataset** to enhance transcription accuracy for Hindi speech, including real-time streaming applications.
+
+## Model Details
+
+### Model Description
+
+- **Model type:** Hybrid ASR model (CTC + Attention)
+- **Model Sample Rate:** 16000 hz
+- **Language(s) (NLP):** Hindi (`hi`)  
+- **License:** Apache-2.0  
+- **Finetuned from model [optional]:** `nvidia/stt_en_fastconformer_hybrid_large_streaming_multi`  
+
+
+
+## **How to Get Started with the Model**
+
+You can load and use the model with the following code:
+
+```python
+import nemo.collections.asr as nemo_asr
+asr_model = nemo_asr.models.EncDecHybridRNNTCTCBPEModel.from_pretrained(model_name="salesken/Hindi-FastConformer-Streaming-ASR")
+
+# Optional: change the default latency. Default latency is 1040ms. Supported latencies: {0: 0ms, 1: 80ms, 16: 480ms, 33: 1040ms}.
+# Note: These are the worst latency and average latency would be half of these numbers.
+asr_model.encoder.set_default_att_context_size([70,13]) 
+
+#Optional: change the default decoder. Default decoder is Transducer (RNNT). Supported decoders: {ctc, rnnt}.
+asr_model.change_decoding_strategy(decoder_type='rnnt')
+
+asr_model.transcribe(['2086-149220-0033.wav'])