Update README.md

README.md

@@ -32,6 +32,14 @@ training time was approximately 12 hours on eight DGX A100 80GB GPUs.
 
 - **License**: cc-by-nc-sa-4.0
 
+## Model Release Date
+
+**LISAT-7B**: TBD
+
+### Status:
+This is a static model trained on a curated geospatial dataset. Future versions of the model will be released as we incorporate community feedback and improve model performance, especially with regards to safety and generalization in remote-sensing image tasks.
+
+
 ## Comparative Performance of LISAT-7B on GRES
 
 The following table shows a comparison of LISAT-7B against LISA-7B and LISA-13B-Llama2-v1 on the GRES dataset across different object sizes. LISAT-7B consistently outperforms the baseline models, particularly in the Small object category.
@@ -62,6 +70,7 @@ pip install --upgrade transformers
 
 Once your installation is updated, you can use LISAT-7B for inference as follows:
 
+```python
 from transformers import AutoModelForImageSegmentation, AutoTokenizer
 
 # Load model and tokenizer
@@ -76,6 +85,7 @@ inputs = tokenizer(input_image, return_tensors="pt")
 outputs = model.generate(**inputs)
 
 
+
 ## Intended Use
 
 ### Intended Use Cases
@@ -86,9 +96,50 @@ Additionally, LISAT-7B can be adapted for various **natural language processing*
 ### Out-of-scope Use
 LISAT-7B is **not** intended for use in any applications that violate applicable laws or regulations, including trade compliance and data protection laws. Use in any way that violates the **Acceptable Use Policy** or the **LISAT Community License** is prohibited. Additionally, any use of LISAT-7B beyond the supported **remote-sensing imagery** tasks outlined in this model card, including use in unsupported domains or languages, is not permitted.
 
+## Responsibility & Safety
+
+As part of our responsible release approach, we followed a multi-pronged strategy to manage trust and safety risks in LISAT-7B:
+
+1. **Enable developers** to deploy helpful, safe, and flexible experiences tailored to their target audience and the specific use cases supported by LISAT-7B.
+2. **Protect developers** against adversarial users who may attempt to exploit the model's capabilities for harmful purposes.
+3. **Provide safeguards** for the community to help prevent the misuse of LISAT-7B, ensuring responsible use in remote-sensing applications.
+
+### Responsible Deployment
+
+LISAT-7B is a model designed to be used in various geospatial tasks, particularly remote-sensing applications. Our approach is focused on building helpful models that enable the world to benefit from the power of this technology, while aligning model safety with generic use cases to address a standard set of risks and harms.
+
+Developers are encouraged to tailor safety measures specific to their use cases, defining their own policies and deploying LISAT-7B with the necessary safeguards in their systems. LISAT-7B was developed following best practices outlined in our Responsible Use Guide. You can refer to the [Responsible Use Guide](#) to learn more about how to implement and enforce these safety practices in your deployment.
+
+## Critical and Other Risks
+
+We specifically focused our efforts on mitigating the following critical risk areas:
+
+1. **Geospatial Misuse**
+   We conducted risk assessments to evaluate whether **LISAT-7B** could be exploited by malicious actors for harmful purposes, such as generating misleading or inaccurate geospatial interpretations that may contribute to dangerous decision-making in critical applications (e.g., military or surveillance purposes).
+
+2. **Environmental Impact**
+   Given the model's domain in remote-sensing imagery, we performed analyses to assess whether **LISAT-7B** could potentially misinterpret environmental data, leading to unsafe or harmful recommendations related to climate or natural resource management.
+
+3. **Privacy and Security Risks**
+   As **LISAT-7B** processes and analyzes images, we ensured that the model does not inadvertently expose sensitive or personal data, adhering to privacy standards and avoiding the generation of harmful insights from publicly or privately sourced imagery.
+
+4. **Model Bias in Object Segmentation**
+   Our evaluation includes assessing whether **LISAT-7B** exhibits bias in its segmentation or interpretation of geospatial data across various terrains, object types, or demographics. We worked with domain experts to ensure that the model's performance is accurate and fair, minimizing biases that could affect decision-making in areas like land use planning or environmental protection.
+
+### Community
+
+Generative AI safety requires ongoing expertise and collaboration, and we believe in the strength of the open community to accelerate progress in this area. We encourage contributions and collaboration within open consortiums focused on AI safety and responsible model deployment. We also engage with communities through relevant standards, including the MLCommons safety evaluation framework.
+
+We invite the community to contribute to the ongoing development of **LISAT-7B**, and we provide an open-source toolset to help developers assess and deploy the model in a safe and responsible manner.
+
+### Ethical Considerations and Limitations
+
+**LISAT-7B** has been designed to be helpful and inclusive in remote-sensing applications. It is meant to serve a wide range of use cases, from environmental monitoring to urban planning, while addressing user needs without unnecessary judgment or normativity. We are committed to ensuring that the model reflects diverse perspectives, especially when it comes to interpreting sensitive data.
+
+However, like any technology, **LISAT-7B** comes with inherent risks. Testing conducted thus far cannot cover every possible scenario. As a result, the model may sometimes generate inaccurate, biased, or otherwise inappropriate outputs, particularly in complex geospatial or ambiguous settings. Developers using **LISAT-7B** for their applications should perform extensive safety testing and fine-tuning tailored to their specific use case to ensure responsible and ethical deployment.
+
+Please, use **LISAT-7B** responsibly.
 
 
-## Example Template
 
-To help users understand the model's directory structure, here's an example of the files and their sizes as shown in the repository: