Update README.md

README.md

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----
-{}
----
-from pathlib import Path
-
-# Path to save the README.md file
-readme_path = Path(r"D:\Programming Folder\Fine-Tune Whisper\Whisper Fine-Tuning By loading Our Model\README.md")
-
-# Content for the README.md file
-readme_content = """
----
-language:
-  - kal
-license: mit
-metrics:
-  - wer
-model_name: Whisper Tiny Fine-tuned on Kalaallisut
-tags:
-  - whisper
-  - automatic-speech-recognition
-  - speech-to-text
-  - kalaallisut
----
-
-# Whisper Tiny Fine-tuned on Kalaallisut
-
-This model is a fine-tuned version of the [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on a very small dataset of the Kalaallisut (Greenlandic) language. Whisper is a general-purpose speech recognition model trained on a large-scale dataset. However, this fine-tuned version on Kalaallisut is **not fully reliable** due to the limited amount of training data.
-
-### Model Details
-
-- **Model**: Whisper Tiny Fine-tuned on Kalaallisut
-- **Base Model**: [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny)
-- **Training Data**: A very small amount of audio-transcription pairs in Kalaallisut
-- **Purpose**: Speech-to-text for the Kalaallisut language
-- **License**: [MIT License](https://opensource.org/licenses/MIT)
-
-### Training Data
-
-This model was fine-tuned on a small dataset of the Kalaallisut language. The dataset was **not comprehensive** and **does not cover all aspects** of the language. As a result, the model is not reliable for general use cases and may produce incorrect transcriptions.
-
-### Limitations
-
-- The model has been trained on a **very small dataset** (only a few hours of audio).
-- The **transcriptions may not be accurate**, especially for more complex audio inputs.
-- This model is a **proof of concept** and not intended for production use.
-
-### Intended Use
-
-The model can be used for:
-
-- Experimentation and testing with Kalaallisut language speech-to-text tasks.
-- It may be helpful for small projects or as a foundation for further fine-tuning with more data.
-
-### Usage Example
-
-You can use the model for transcription with the following code:
-
-```python
-from transformers import WhisperProcessor, WhisperForConditionalGeneration
-import torch
-
-# Load the model and processor
-processor = WhisperProcessor.from_pretrained("VoiceLessQ/whisper-tiny-kalaallisut")
-model = WhisperForConditionalGeneration.from_pretrained("VoiceLessQ/whisper-tiny-kalaallisut")
-
-# Load and process an audio file
-audio_array = ...  # Load your audio file here
-input_features = processor(audio_array, sampling_rate=16000, return_tensors="pt").input_features
-
-# Generate transcription
-generated_ids = model.generate(input_features)
-transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
-
-print(f"Transcription: {transcription}")
+# Whisper Tiny Fine-tuned on Kalaallisut
+
+This model is a fine-tuned version of the [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on a very small dataset of the Kalaallisut (Greenlandic) language. Whisper is a general-purpose speech recognition model trained on a large-scale dataset. However, this fine-tuned version on Kalaallisut is **not fully reliable** due to the limited amount of training data.
+
+### Model Details
+
+- **Model**: Whisper Tiny Fine-tuned on Kalaallisut
+- **Base Model**: [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny)
+- **Training Data**: A very small amount of audio-transcription pairs in Kalaallisut
+- **Purpose**: Speech-to-text for the Kalaallisut language
+- **License**: [MIT License](https://opensource.org/licenses/MIT)
+
+### Training Data
+
+This model was fine-tuned on a small dataset of the Kalaallisut language. The dataset was **not comprehensive** and **does not cover all aspects** of the language. As a result, the model is not reliable for general use cases and may produce incorrect transcriptions.
+
+### Limitations
+
+- The model has been trained on a **very small dataset** (only a few hours of audio).
+- The **transcriptions may not be accurate**, especially for more complex audio inputs.
+- This model is a **proof of concept** and not intended for production use.
+
+### Intended Use
+
+The model can be used for:
+
+- Experimentation and testing with Kalaallisut language speech-to-text tasks.
+- It may be helpful for small projects or as a foundation for further fine-tuning with more data.
+
+### Usage Example
+
+You can use the model for transcription with the following code:
+
+```python
+from transformers import WhisperProcessor, WhisperForConditionalGeneration
+import torch
+
+# Load the model and processor
+processor = WhisperProcessor.from_pretrained("VoiceLessQ/whisper-tiny-kalaallisut")
+model = WhisperForConditionalGeneration.from_pretrained("VoiceLessQ/whisper-tiny-kalaallisut")
+
+# Load and process an audio file
+audio_array = ...  # Load your audio file here
+input_features = processor(audio_array, sampling_rate=16000, return_tensors="pt").input_features
+
+# Generate transcription
+generated_ids = model.generate(input_features)
+transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+
+print(f"Transcription: {transcription}")