updated template

README.md

@@ -1,5 +1,5 @@
 ---
-license: cc-by-4.0
+license: apache-2.0
 language:
 - 'no'
 - nb
@@ -9,6 +9,7 @@ datasets:
 - NbAiLab/ncc_speech
 - NbAiLab/NST
 - NbAiLab/NPSC
+base_model: openai/whisper-large
 tags:
 - audio
 - asr
@@ -39,27 +40,38 @@ Introducing the **_Norwegian NB-Whisper Large model_**, proudly developed by the
       <source src="https://huggingface.co/NbAiLab/nb-whisper-small-beta/resolve/main/king.mp4" type="video/mp4">
     Your browser does not support the video tag.
     </video>   
-  <figcaption><a href="https://www.royalcourt.no/tale.html?tid=137662&sek=28409&scope=27248" target="_blank">Speech given by His Majesty The King of Norway at the garden party hosted by Their Majesties The King and Queen at the Palace Park on 1st of September 2016.</a>Transcribed using the Small model.</figcaption>
+  <figcaption><a href="https://www.royalcourt.no/tale.html?tid=137662&sek=28409&scope=27248" target="_blank">Speech given by His Majesty The King of Norway at the garden party hosted by Their Majesties The King and Queen at the Palace Park on 1st of September 2016.</a> Transcribed using the Small model.</figcaption>
 </figure> 
 </center>
 
 
 ## Model Details
 
-The NB-Whisper series offers models in five distinct sizes: Tiny, Base, Small, Medium, and Large, each designed to cater to different requirements. We generally recommend the Main models for most users, as they are balanced for common use cases. Additionally, there are two variants available for each size:
+The NB-Whisper series offers models in five distinct sizes: Tiny, Base, Small, Medium, and Large, each designed to cater to different requirements. These models are balanced for common use cases.
+
+
+| Model Size | Parameters | Model |
+|------------|------------|------------|
+| Tiny       | 39M        | [NB-Whisper Tiny](https://huggingface.co/NbAiLabBeta/nb-whisper-tiny) |
+| Base       | 74M        | [NB-Whisper Base](https://huggingface.co/NbAiLabBeta/nb-whisper-base) |
+| Small      | 244M       | [NB-Whisper Small](https://huggingface.co/NbAiLabBeta/nb-whisper-small) |
+| Medium     | 769M       | [NB-Whisper Medium](https://huggingface.co/NbAiLabBeta/nb-whisper-medium) |
+| Large      | 1550M      | [NB-Whisper Large](https://huggingface.co/NbAiLabBeta/nb-whisper-large) |
+
+Additionally, there are two variants available for each size:
 
 - **Verbatim version**: This lower-cased variant is more literal and suitable for tasks requiring detailed transcription, such as linguistic analysis.
 - **Semantic version**: This variant focuses less on verbatim accuracy but captures the essence of content, ideal for meeting minutes and subtitling.
 
 All models are used in the same manner. Here are the available models:
 
-| Model Size | Parameters | Main Model | Verbatim version | Semantic version |
-|------------|------------|------------|------------------|------------------|
-| Tiny       | 39M        | [NB-Whisper Tiny](https://huggingface.co/NbAiLabBeta/nb-whisper-tiny) | [Tiny - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-tiny-verbatim) | [Tiny - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-tiny-semantic) |
-| Base       | 74M        | [NB-Whisper Base](https://huggingface.co/NbAiLabBeta/nb-whisper-base) | [Base - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-base-verbatim) | [Base - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-base-semantic) |
-| Small      | 244M       | [NB-Whisper Small](https://huggingface.co/NbAiLabBeta/nb-whisper-small) | [Small - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-small-verbatim) | [Small - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-small-semantic) |
-| Medium     | 769M       | [NB-Whisper Medium](https://huggingface.co/NbAiLabBeta/nb-whisper-medium) | [Medium - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-medium-verbatim) | [Medium - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-medium-semantic) |
-| Large      | 1550M      | [NB-Whisper Large](https://huggingface.co/NbAiLabBeta/nb-whisper-large) | [Large - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-large-verbatim) | [Large - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-large-semantic) |
+| Model Size | Parameters | Verbatim version | Semantic version |
+|------------|------------|------------|------------------|
+| Tiny       | 39M        | [Tiny - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-tiny-verbatim) | [Tiny - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-tiny-semantic) |
+| Base       | 74M        | [Base - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-base-verbatim) | [Base - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-base-semantic) |
+| Small      | 244M       | [Small - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-small-verbatim) | [Small - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-small-semantic) |
+| Medium     | 769M       | [Medium - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-medium-verbatim) | [Medium - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-medium-semantic) |
+| Large      | 1550M      | [Large - verbatim](https://huggingface.co/NbAiLabBeta/nb-whisper-large-verbatim) | [Large - semantic](https://huggingface.co/NbAiLabBeta/nb-whisper-large-semantic) |
 
 
 Please refer to the OpenAI Whisper model card for more details about the backbone model.
@@ -70,7 +82,7 @@ Please refer to the OpenAI Whisper model card for more details about the backbon
 - **Shared by:** [NB AI-Lab](https://ai.nb.no/)
 - **Model type:** `whisper`
 - **Language(s) (NLP):** Norwegian, Norwegian Bokmål, Norwegian Nynorsk, English
-- **License:** [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)
+- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
 - **Trained from model:** [openai/whisper-large](https://huggingface.co/openai/whisper-large)
 - **Code Repository:** https://github.com/NbAiLab/nb-whisper/
 - **Paper:** _Coming soon_
@@ -86,10 +98,10 @@ Alternatively, you can download the models for local usage. The Tiny, Base, and
 
 ```bash
 # Download the sample file
-> wget -N https://github.com/NbAiLab/nb-whisper/raw/main/audio/king.mp3
+$ wget -N https://github.com/NbAiLab/nb-whisper/raw/main/audio/king.mp3
 
 # Install necessary libraries. 
-> pip install transformers>=4.35.2
+$ pip install transformers>=4.35.2
 ```
 
 After this is done, you should be able to run this in Python:
@@ -169,10 +181,12 @@ asr("king.mp3", chunk_length_s=30, return_timestamps=True, generate_kwargs={'tas
 </details>
 
 Some other cool features to look into:
+
 ```python
 # Transcribe to Nynorsk
 asr("king.mp3", chunk_length_s=30, generate_kwargs={'task': 'transcribe', 'language': 'nn'})
 ```
+
 <details>
 <summary>Expected output</summary>
 
@@ -221,7 +235,24 @@ asr("king.mp3", chunk_length_s=30, return_timestamps="word", generate_kwargs={'t
 ### Whisper CPP
 Whisper CPP is a C++ implementation of the Whisper model, offering the same functionalities with the added benefits of C++ efficiency and performance optimizations. This allows embedding any Whisper model into a binary file, facilitating the development of real applications. However, it requires some familiarity with compiling C++ programs. Their [homepage](https://github.com/ggerganov/whisper.cpp) provides examples of how to build applications, including real-time transcription. 
 
-We have converted this model to the ggml-format model used by Whisper CPP binaries. The file can be downloaded [here](blob/main/ggml-model.bin).
+We have converted this model to the ggml-format model used by Whisper CPP binaries. The file can be downloaded [here](blob/main/ggml-model.bin), and a `q5_0` quantized version is also available [here](blob/main/ggml-model-q5_0.bin).
+
+```bash
+# We can download and compile whisper.cpp
+$ git clone --depth 1 https://github.com/ggerganov/whisper.cpp --branch v1.5.1
+$ cd whisper.cpp/
+$ make
+
+# We also need to convert the audio to WAV as that is the only format supported by whisper.cpp
+$ wget -N https://github.com/NbAiLab/nb-whisper/raw/main/audio/king.mp3
+$ ffmpeg -i king.mp3 -ar 16000 -ac 1 -c:a pcm_s16le king.wav                                        
+
+# And run it with the f16 default model
+$ ./main -m /path/to/ggml-model.bin king.wav
+
+# Or the quantized version
+$ ./main -m /path/to/ggml-model-q5_0.bin king.wav
+```
 
 ### API
 Instructions for accessing the models via a simple API are included in the demos under Spaces. Note that these demos are temporary and will only be available for a few weeks.
@@ -243,10 +274,14 @@ The models, especially the smaller ones, may exhibit occasional hallucinations a
 Using these models without adequate risk assessment and mitigation could be considered irresponsible. They may contain biases or other undesirable distortions. Users who deploy these models or integrate them into systems or services are responsible for mitigating risks and complying with applicable AI regulations. The National Library of Norway, as the model owner, disclaims liability for any outcomes resulting from third-party use of these models.
 
 ### Software
-The model is trained using Jax/Flax and converted to Pytorch, Tensorflow, whisper.cpp, and ONXX formats. These are available under `Files and versions`. We welcome requests for conversion to other formats.
+The model was trained using Jax/Flax and converted to PyTorch, Tensorflow, whisper.cpp, and ONXX formats. These are available under `Files and versions`. We welcome requests for conversion to other formats. All training code and scripts are released under the Apache License 2.0 in the GitHub repository [nb-whisper](https://github.com/NbAiLab/nb-whisper/).
 
 ## Citation & Contributors
-The NB-Whisper Large model is a product of the NoSTram project led by Per Egil Kummervold (PEK) at the National Library of Norway. Key contributors include Javier de la Rosa (JdlR), Freddy Wetjen (FW), Rolv-Arild Braaten (RAB), and PEK. AiLab, under the direction of Svein Arne Brygfjeld, supported the project's successful completion. A detailed paper on our process and findings is forthcoming.
+The NB-Whisper Large model is a product of the NoSTram project led by Per Egil Kummervold ([@pere](https://huggingface.co/pere) at the National Library of Norway. Key contributors include Javier de la Rosa ([@versae](https://huggingface.co/versae), Freddy Wetjen ([@](https://huggingface.co/freddyw), and Rolv-Arild Braaten ([@Rolv-Arild](https://huggingface.co/Rolv-Arild). NB AI-Lab, under the direction of Svein Arne Brygfjeld ([@Brygfjeld](https://huggingface.co/Brygfjeld), supported the project's successful completion. A detailed paper on our process and findings is forthcoming.
+
+## Disclaimer
+
+The models published in this repository are intended for a generalist purpose and are available to third parties. These models may have bias and/or any other undesirable distortions. When third parties, deploy or provide systems and/or services to other parties using any of these models (or using systems based on these models) or become users of the models, they should note that it is their responsibility to mitigate the risks arising from their use and, in any event, to comply with applicable regulations, including regulations regarding the use of artificial intelligence. In no event shall the owner of the models (The National Library of Norway) be liable for any results arising from the use made by third parties of these models.
 
 ## Acknowledgements