Improve dataset card: Add paper, code, Gradio space links, and update metadata

This PR significantly improves the dataset card for `mshamrai/language-metric-data` by:
- Adding a link to the associated paper ([https://huggingface.co/papers/2508.11676](https://huggingface.co/papers/2508.11676)).
- Adding a link to the GitHub repository ([https://github.com/mshamrai/deep-language-geometry](https://github.com/mshamrai/deep-language-geometry)).
- Adding a link to the Hugging Face Space for analysis ([https://huggingface.co/spaces/mshamrai/language-metric-analysis](https://huggingface.co/spaces/mshamrai/language-metric-analysis)).
- Specifying the `feature-extraction` task category and relevant tags (`multilingual`, `llm`, `linguistics`, `embeddings`).
- Updating the license from Apache 2.0 to MIT, as stated in the project's GitHub repository.
- Providing a clear description of the dataset's content and purpose, derived from the paper's abstract and GitHub README.

README.md

@@ -1,3 +1,26 @@
----
-license: apache-2.0
----
+---
+license: mit
+task_categories:
+- feature-extraction
+tags:
+- multilingual
+- llm
+- linguistics
+- embeddings
+---
+
+This dataset contains the computed language latent vectors (binary vectors, Euclidean vectors, and distances) as presented in the paper [Deep Language Geometry: Constructing a Metric Space from LLM Weights](https://huggingface.co/papers/2508.11676).
+
+The paper introduces a novel framework that utilizes the internal weight activations of Large Language Models (LLMs) to construct a metric space of languages. This dataset makes the automatically derived high-dimensional vector representations for 106 languages publicly available, capturing intrinsic language characteristics that reflect linguistic phenomena.
+
+**Paper:** [Deep Language Geometry: Constructing a Metric Space from LLM Weights](https://huggingface.co/papers/2508.11676)
+**Code:** [https://github.com/mshamrai/deep-language-geometry](https://github.com/mshamrai/deep-language-geometry)
+**Gradio Analysis Tool (Hugging Face Space):** [https://huggingface.co/spaces/mshamrai/language-metric-analysis](https://huggingface.co/spaces/mshamrai/language-metric-analysis)
+
+### Dataset Contents
+The dataset includes:
+- Calculated binary vectors
+- Euclidean vectors
+- Distances between languages
+
+These components can be used to analyze and visualize inter-language connections and linguistic families.