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Update README.md

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@@ -30,21 +30,21 @@ This modelcard aims to be a base template for new models. It has been generated
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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  - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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  ### Model Sources [optional]
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  <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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  ## Uses
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  <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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  ### Downstream Use [optional]
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  <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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  ### Out-of-Scope Use
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  <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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  ## Bias, Risks, and Limitations
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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  ### Recommendations
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  ## How to Get Started with the Model
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- Use the code below to get started with the model.
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-
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- [More Information Needed]
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  ## Training Details
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  <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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- [More Information Needed]
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  ### Training Procedure
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  #### Preprocessing [optional]
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- [More Information Needed]
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  #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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  #### Speeds, Sizes, Times [optional]
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  <!-- This should link to a Dataset Card if possible. -->
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- [More Information Needed]
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  #### Factors
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  <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- [More Information Needed]
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  ### Results
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- [More Information Needed]
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  #### Summary
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  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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  ## Technical Specifications [optional]
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  ### Model Architecture and Objective
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- [More Information Needed]
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  ### Compute Infrastructure
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- [More Information Needed]
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  #### Hardware
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- [More Information Needed]
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  #### Software
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- [More Information Needed]
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  ## Citation [optional]
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  **BibTeX:**
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- [More Information Needed]
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  **APA:**
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- [More Information Needed]
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  ## Glossary [optional]
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  <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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- [More Information Needed]
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  ## More Information [optional]
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- [More Information Needed]
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  ## Model Card Authors [optional]
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- [More Information Needed]
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  ## Model Card Contact
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- [More Information Needed]
 
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+ - **Developed by:** Md Safwan Abdullah
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+ - **Funded by [optional]:**
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+ - **Shared by [optional]:**
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  - **Model type:** [More Information Needed]
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+ - **Language(s) (NLP):** Bangla and English
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+ - **License:** license: afl-3.0
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+ - **Finetuned from model [optional]:**
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  ### Model Sources [optional]
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  <!-- Provide the basic links for the model. -->
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+ - **Repository:**
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+ - **Paper [optional]:**
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+ - **Demo [optional]:**
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  ## Uses
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  <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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+ [
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  ### Downstream Use [optional]
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  <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+ [
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  ### Out-of-Scope Use
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  <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+ [
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  ## Bias, Risks, and Limitations
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+ [
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  ### Recommendations
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  ## How to Get Started with the Model
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+ Just start chatting.
 
 
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  ## Training Details
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  <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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+ [
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  ### Training Procedure
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  #### Preprocessing [optional]
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+ [
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  #### Training Hyperparameters
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+ - **Training regime:** [ <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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  #### Speeds, Sizes, Times [optional]
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  <!-- This should link to a Dataset Card if possible. -->
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+ [
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  #### Factors
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  <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+ [
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  ### Results
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+ [
 
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  #### Summary
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  Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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+ - **Hardware Type:** All
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+ - **Hours used:**
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+ - **Cloud Provider:**
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+ - **Compute Region:**
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+ - **Carbon Emitted:**
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  ## Technical Specifications [optional]
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  ### Model Architecture and Objective
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+ First Ai Made By in Bangla Language, By a Bangladeshi, For All.
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  ### Compute Infrastructure
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+ .
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  #### Hardware
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+ [
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  #### Software
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+ [
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  ## Citation [optional]
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  **BibTeX:**
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+ [
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  **APA:**
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+ [
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  ## Glossary [optional]
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  <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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+ [
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  ## More Information [optional]
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+ [
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  ## Model Card Authors [optional]
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+ [
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  ## Model Card Contact
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+ [