Update README.md

README.md

@@ -24,6 +24,53 @@ extra_gated_button_content: Acknowledge license
 This model was converted to GGUF format from [`google/txgemma-9b-chat`](https://huggingface.co/google/txgemma-9b-chat) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/google/txgemma-9b-chat) for more details on the model.
 
+---
+TxGemma is a collection of lightweight, state-of-the-art, open language models
+built upon Gemma 2, fine-tuned for therapeutic development. It comes in 3 sizes,
+2B, 9B, and 27B.
+
+TxGemma models are designed to process and understand information related to
+various therapeutic modalities and targets, including small molecules, proteins,
+nucleic acids, diseases, and cell lines. TxGemma excels at tasks such as
+property prediction, and can serve as a foundation for further fine-tuning or as
+an interactive, conversational agent for drug discovery. The model is fine-tuned
+from Gemma 2 using a diverse set of instruction-tuning datasets, curated from
+the Therapeutics Data Commons (TDC).
+
+TxGemma is offered as both a prediction model that expects a narrow form of
+prompting and for the 9B and 27B version, conversational models that are more
+flexible and can be used in multi-turn interactions, including to explain its
+rationale behind a prediction. This conversational model comes at the expense of
+some raw prediction performance. See our manuscript
+for more information.
+
+Key Features
+-
+-Versatility: Exhibits strong performance across a wide range of therapeutic
+tasks, outperforming or matching best-in-class performance on a significant
+number of benchmarks.
+
+-Data Efficiency: Shows competitive performance even with limited data
+compared to larger models, offering improvements over its predecessors.
+
+-Conversational Capability (TxGemma-Chat): Includes conversational variants
+that can engage in natural language dialogue and explain the reasoning
+behind their predictions.
+
+-Foundation for Fine-tuning: Can be used as a pre-trained foundation for
+specialized use cases.
+
+Potential Applications
+-
+TxGemma can be a valuable tool for researchers in the
+following areas:
+
+Accelerated Drug Discovery: Streamline the therapeutic development process
+by predicting properties of therapeutics and targets for a wide variety of
+tasks including target identification, drug-target interaction prediction,
+and clinical trial approval prediction.
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)