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--- |
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language: |
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- ar |
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pipeline_tag: text-generation |
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tags: |
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- LLM |
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- ARABIC_LLM |
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- NLP |
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- Pretrained |
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- Transformers |
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- Language-modeling |
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- Multilingual |
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- Text-classification |
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- Question-answering |
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license: cc-by-sa-4.0 |
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--- |
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# ALLaM-7B Model Card |
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<!-- Provide a quick summary of what the model is/does. --> |
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[More Information Needed] |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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- **Model Name:** ALLaM-7B |
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- **Model Type:** Language Model |
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- **Model Size:** 7 billion parameters |
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- **Developed and funded by:** Saudi Authority for Data and Artificial Intelligence |
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- **Language(s) (NLP):** Arabic |
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- **Task(s):** Text Generation, Text Classification, Text Summarization, Question Answering |
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- **Architecture:** [More Information Needed] |
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- **License:** [More Information Needed] |
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- **Training Data:** [List the datasets used for training] |
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- **Training Procedure:** [Briefly describe the training methodology, hardware, and any special techniques like fine-tuning on specific tasks.] |
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- **Finetuned from model [optional]:** [More Information Needed] |
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- **Input Format:** Text (string of characters) |
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- **Output Format:** Text (generated or classified text) |
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- **Maximum Token Length:** [Token limit, e.g., 1024 tokens] |
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- **Pre-training Data:** [Mention any corpora or datasets used during pre-training] |
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- **Fine-tuning:** [Indicate if the model is fine-tuned for specific tasks] |
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- **Intended Use:** |
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ALLaM-7B is designed for a wide range of natural language processing (NLP) tasks, such as: |
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- Text generation |
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- Summarization |
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- Question answering |
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- Language modeling |
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- Text classification |
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- [Other tasks based on the model's capabilities] |
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- **Examples of Use Cases:** |
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- Conversational AI |
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- Content creation tools |
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- Automatic summarization tools |
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- Question answering systems |
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- Sentiment analysis |
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- [Include any other relevant use cases] |
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- **Performance:** |
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• Benchmarking: [Provide performance metrics on popular NLP benchmarks] |
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• Accuracy: [List any accuracy results for downstream tasks] |
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• Inference Speed: [Include any details on inference latency and speed] |
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- **Limitations:** |
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• Bias and Fairness: As with many large-scale models, ALLaM-7B may exhibit biases present in the training data. |
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• Generalization: The model may not generalize well on highly domain-specific tasks without further fine-tuning. |
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• Complexity: Due to its size (7 billion parameters), the model requires substantial computational resources for inference and fine-tuning. |
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- **Ethical Considerations:** |
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• Potential for Misuse: Like other large language models, ALLaM-7B could be used to generate harmful, misleading, or biased content if not monitored properly. |
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• Biases: The model could reflect and perpetuate harmful stereotypes or biases present in the training data. Users should take care when deploying it in sensitive applications. |
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- **Acknowledgments:** |
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• This model is based on Transformer Architecture and was trained on large-scale datasets like [Dataset Name(s)]. |
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• Special thanks to the [SDAIA ALLaM Research Lab] for their work in developing this model. |
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- **Citation:** |
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If you use ALLaM-7B in your work, please cite the following: |
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scss |
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Copy code |
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@inproceedings{Allam2025, |
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title={ALLaM-7B: A 7 Billion Parameter Transformer for General NLP Tasks}, |
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author={SDAIA ALLaM Research Lab}, |
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year={2025}, |
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booktitle={Proceedings of the NLP Conference}, |
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} |
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[More Information Needed] |
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- **License:** |
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• License: CC-BY-SA-4.0 |
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• Model Availability: Available for research and commercial use under the terms of the CC-BY-SA-4.0 license. Please ensure attribution and share alike when redistributing or modifying the model. |
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- **Model Sources:** |
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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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- **How to Use:** |
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- **Install the Required Libraries::** |
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bash |
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Copy code |
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pip install transformers |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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### Direct Use |
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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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### Recommendations |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further 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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[More Information Needed] |
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## Training Details |
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### Training Data |
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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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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
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#### Speeds, Sizes, Times [optional] |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
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[More Information Needed] |
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## Evaluation |
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<!-- This section describes the evaluation protocols and provides the results. --> |
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### Testing Data, Factors & Metrics |
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**Testing Data** |
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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 things the evaluation is disaggregating by, e.g., subpopulations or domains. --> |
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[More Information Needed] |
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#### Metrics |
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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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## Model Examination [optional] |
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<!-- Relevant interpretability work for the model goes here --> |
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[More Information Needed] |
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## Citation [optional] |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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**APA:** |
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[More Information Needed] |
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## Model Card Contact |
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[More Information Needed] |
