Update README.md

README.md

@@ -10,9 +10,9 @@ library_name: transformers
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 # Fanar-1-9B-Instruct
 
-**Fanar-1-9B-Instruct** is a powerful Arabic-English LLM developed by [Qatar Computing Research Institute (QCRI)](https://www.hbku.edu.qa/en/qcri) and [Hamad Bin Khalifa University (HBKU)](https://www.hbku.edu.qa/). It is the instruction-tuned version of [Fanar-1-9B](). Fanar continually pretrains the `google/gemma-2-9b` model on 1T Arabic and English tokens. Fanar pays particular attention to the richness of the Arabic language by supporting a diverse set of Arabic dialects including Modern Standard Arabic (MSA), Levantine, and Egyptian. Fanar, through meticulous curation of the pretraining and instruction-tuning data, is aligned with Arab cultural values.
+**Fanar-1-9B-Instruct** is a powerful Arabic-English LLM developed by [Qatar Computing Research Institute (QCRI)](https://www.hbku.edu.qa/en/qcri) at [Hamad Bin Khalifa University (HBKU)](https://www.hbku.edu.qa/), a member of Qatar Foundation for Education, Science, and Community Development. It is the instruction-tuned version of [Fanar-1-9B](). Fanar continually pretrains the `google/gemma-2-9b` model on 1T Arabic and English tokens. Fanar pays particular attention to the richness of the Arabic language by supporting a diverse set of Arabic dialects including Modern Standard Arabic (MSA), Levantine, and Egyptian. Fanar, through meticulous curation of the pretraining and instruction-tuning data, is aligned with Arab cultural values.
 
-**Fanar-1-9B-Instruct** is a core component within the [Fanar GenAI platform](https://chat.fanar.qa/) that offers a suite of capabilities including image generation, video and image understanding, deep thinking, advanced text-to-speech (TTS) and automatic-speech-recognition (ASR), attribution and fact-checking, Islamic RAG, among several other features.
+**Fanar-1-9B-Instruct** is a core component within the [Fanar GenAI platform](https://fanar.qa/) that offers a suite of capabilities including image generation, video and image understanding, deep thinking, advanced text-to-speech (TTS) and automatic-speech-recognition (ASR), attribution and fact-checking, Islamic RAG, among several other features.
 
 We have published a comprehensive [report](https://arxiv.org/pdf/2501.13944) with all the details regarding FANAR. We also provide an API to the model and our GenAI platform (request access [here](https://api.fanar.qa/request/en)).
 
@@ -98,7 +98,7 @@ Fanar is intended to be deployed as part of a broader AI system. Developers are
 
 ## Ethical Considerations & Limitations
 
-Fanar is capable of generating fluent and contextually appropriate responses, but as with any generative model there are uncertainities. The model may produce **biased, offensive, or incorrect outputs**. The model should It is **not suitable for high-stakes decision making** (e.g., legal, medical, or financial advice). Though we have extensively tested Fanar and attempted to mitigate these issues, we cannot redress every possible scenario. Thus, we advise developers to implement safety checks and perform domain-specific fine-tuning for sensitive use cases.
+Fanar is capable of generating fluent and contextually appropriate responses, but as with any generative model there are uncertainities. The model may produce **biased, offensive, or incorrect outputs**. The model should It is **not suitable for high-stakes decision making** (e.g., legal, medical, or financial advice). Though we have extensively tested Fanar and attempted to mitigate these issues, we cannot redress every possible scenario. Thus, we advise developers to implement safety checks and perform domain-specific fine-tuning for sensitive use cases. Kindly refer to our [Terms of Service]( https://chat.fanar.qa/terms-of-service) and [Privacy Policy](https://chat.fanar.qa/privacy-policy).
 
 The output generated by this model is not considered a statement of QCRI, HBKU, or any other organization or individual.
  
@@ -128,7 +128,7 @@ Evaluation was conducted using a modified version of the LM Evaluation Harness a
 | AceGPT-v2-8B-Chat | 66.45% | 51.16% | 62.61% | 79.21% | 80.58% | 53.50% | 74.56% | 77.66% | 41.77% | 50.16% | 60.40% | 74.31% | 68.90% | 64.58% | 61.32% | 56.91% | 54.53% | 53.91% |
 | gemma-2-9b-it | 71.65% | 57.93% | 64.16% | 79.06% | 79.38% | 63.99% | 78.31% | **80.67%** | 60.95% | 56.11% | 64.21% | 73.69% | 68.60% | 61.26% | 59.96% | 57.24% | 57.95% | 59.25% |
 | jais-adapted-13b-chat | 56.64% | 44.45% | 58.97% | 80.86% | 80.47% | 54.27% | 67.52% | 75.24% | 44.05% | 46.41% | 56.56% | 65.46% | 65.30% | 61.10% | 58.05% | 55.77% | 52.87% | 53.59% |
-| jais-family-6p7b-chat | 49.42% | 41.59% | 55.80% | 72.04% | 74.05% | 44.62% | 65.11% | 72.04% | 53.68% | 48.20% |    TBD    | 61.72% | 64.10% | 62.51% | 60.12% | 57.24% | 49.11% | 47.49% |
+| jais-family-6p7b-chat | 49.42% | 41.59% | 55.80% | 72.04% | 74.05% | 44.62% | 65.11% | 72.04% | 53.68% | 48.20% |    54.73%    | 61.72% | 64.10% | 62.51% | 60.12% | 57.24% | 49.11% | 47.49% |
 | Llama-3.1-8B-Instruct | 68.04% | 47.58% | 59.05% | 79.22% | 80.74% | 55.29% | 66.72% | 76.67% | 29.26% | 47.81% |    TBD    | 69.70% | 66.10% | 58.11% | 55.39% | 54.24% | 46.86% | 47.52% |
 | Qwen2.5-7B-Instruct | **74.21%** | 55.63% | 63.96% | 80.44% | 79.92% | 55.03% | 74.61% | 78.09% | 71.34% | 54.19% | 62.69% | 75.69% | 68.10% | 60.55% | 58.65% | 56.04% | 48.74% | 53.42% |
 
@@ -156,7 +156,9 @@ If you use Fanar in your research or applications, please cite:
 
 ## Acknowledgements
 
-This project is a collaboration between [Qatar Computing Research Institute (QCRI)](https://qcri.org) and [Hamad Bin Khalifa University (HBKU)](https://hbku.edu.qa). We thank our engineering and research teams for their efforts in advancing Arabic-centric large language models.
+This project is an effort by the [Qatar Computing Research Institute (QCRI)](https://qcri.org), part of [Hamad Bin Khalifa University (HBKU)](https://hbku.edu.qa). We thank our engineering and research teams for their efforts in advancing Arabic-centric large language models.
+We thank the [MCIT](https://www.mcit.gov.qa/en/) for sponsoring this project and their continued support by providing the compute infrastructure.
+
 
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