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README.md

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-This Model Performs Language Identification for all South African languages (Sepedi (nso), Sesotho(sot), Setswana(tsn), Xitsonga(tso), Isindebele(nr), Tshivenda(ven), IsiXhosa(xho), IsiZulu(zul), IsiSwati(ssw), Afrikaans(af), and English(en)).
+---
+# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/model-cards
+{}
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** Thapelo Sindane
+- **Shared by [optional]:** DSFSI
+- **Model type:** BERT
+- **Language(s) (NLP):** Sepedi (nso), Sesotho(sot), Setswana(tsn), Xitsonga(tso), Isindebele(nr), Tshivenda(ven), IsiXhosa(xho), IsiZulu(zul), IsiSwati(ssw), Afrikaans(af), and English(en)
+- **License:** CC
+- **Finetuned from model [optional]:** N/A
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+Models must be used for language identification of the South African languages identified above
+
+### Direct Use
+
+LID for low-resourced languages
+
+### Downstream Use [optional]
+
+Language data filtering and identification
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+Language detection in code-switched data.
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+Requires GPU to run fast
+
+[More Information Needed]
+
+### Recommendations
+
+Do not use for sensitive tasks. Model at an infant stage.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+
+
+
+## Training Details
+
+### Training Data
+
 The source data used to train the model came from the paper 'Preparing Vuk...' referenced below:
+* Lastrucci, R., Dzingirai, I., Rajab, J., Madodonga, A., Shingange, M., Njini, D. and Marivate, V., 2023. Preparing the Vuk'uzenzele and ZA-gov-multilingual South African multilingual corpora. arXiv preprint arXiv:2303.03750.
+
+Number of sentences in datasets:
+'nso': 5007,
+'tsn': 4851,
+'sot': 5075,
+'xho': 5219,
+'zul': 5103,
+'nbl': 5600,
+'ssw': 5210,
+'ven': 5119,
+'tso': 5193,
+'af': 5252,
+'eng': 5552
+Train Test split: Train: 70% of minimum,  15% of minimum size, Dev: remaining sample
+
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+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).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
 
-# Model:
-The model used is a bert model trained to detect all 11 South African languages. 
- 
+[More Information Needed]
 
-# References
+## Model Card Contact
 
-* Lastrucci, R., Dzingirai, I., Rajab, J., Madodonga, A., Shingange, M., Njini, D. and Marivate, V., 2023. Preparing the Vuk'uzenzele and ZA-gov-multilingual South African multilingual corpora. arXiv preprint arXiv:2303.03750.
+[More Information Needed]