Populate Model Card with details

This pull request populates the automatically generated model card with details from the provided context. It adds the pipeline tag, library name and license. It also includes links to the Hugging Face paper page and the presumed GitHub repository. The license should be double-checked and updated if necessary. Further details about the model, its uses, biases, and limitations should be added for completeness.

README.md

@@ -1,70 +1,53 @@
 ---
+pipeline_tag: text-generation
 library_name: transformers
-tags: []
+license: other
 ---
 
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
-
-
+This model is a large language model capable of text generation.  Further details about the model architecture and capabilities are needed.
 
 ## Model Details
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+This is a transformers model for text generation. More information is needed to fully describe this model, including its architecture, training data, and specific capabilities.
 
 - **Developed by:** [More Information Needed]
 - **Funded by [optional]:** [More Information Needed]
 - **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
+- **Model type:** Large Language Model (LLM)
 - **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
+- **License:** other
 - **Finetuned from model [optional]:** [More Information Needed]
 
 ### Model Sources [optional]
 
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
+- **Repository:** [More Information Needed]  *(Presumed GitHub repository)*
+- **Paper [optional]:** [https://huggingface.co/papers/2502.05209](https://huggingface.co/papers/2502.05209)
 - **Demo [optional]:** [More Information Needed]
 
 ## Uses
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
 ### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
 [More Information Needed]
 
 ### Downstream Use [optional]
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
 [More Information Needed]
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
 [More Information Needed]
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
 [More Information Needed]
 
 ### Recommendations
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
 Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
 
 ## How to Get Started with the Model
@@ -77,14 +60,10 @@ Use the code below to get started with the model.
 
 ### Training Data
 
-<!-- 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. -->
-
 [More Information Needed]
 
 ### 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]
@@ -96,32 +75,22 @@ Use the code below to get started with the model.
 
 #### 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
@@ -130,18 +99,14 @@ Use the code below to get started with the model.
 
 #### Summary
 
-
+[More Information Needed]
 
 ## 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]
@@ -170,8 +135,6 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 ## 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]
@@ -182,8 +145,6 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 ## 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]