Update license information in model card

README.md

@@ -1,5 +1,5 @@
 ---
-license: cc0-1.0
+license: cc-by-4.0
 language:
 - en
 base_model: google/gemma-2-2b
@@ -8,8 +8,16 @@ pipeline_tag: text-generation
 tags:
 - biology
 - scRNAseq
-- single-cell
-- gemma-2
+- Gemma-2
+- genomics
+- computational-biology
+- bioinformatics
+- gene-expression
+- cell-biology
+- transformers
+- pytorch
+- cell-type-annotation
+- Question Answering
 ---
 
 # C2S-Scale-Gemma-2B model card
@@ -51,7 +59,7 @@ classification, and generating biologically meaningful cell representations.
 
 *   Versatility: Demonstrates strong performance across a diverse set of single-cell and multi-cell tasks.
 *   Scalability: Trained on a massive dataset of over 57 million cells, showcasing the power of scaling LLMs for biological data.
-*   Generative Power: Capable of generating realistic single-cell gene expression profiles, both conditionally and unconditionally.
+*   Generative Power: Capable of generating realistic single-cell gene expression profiles.
 *   Foundation for Fine-tuning: Can serve as a powerful pretrained foundation for specialized, domain-specific single-cell analysis tasks.
 
 **Potential Applications**
@@ -113,7 +121,7 @@ model = AutoModelForCausalLM.from_pretrained(
 ).to(device)
 
 # Format prompt (see previous section)
-cell_sentence = "MALAT1 TMSB4X B2M EEF1A1 H3F3B ACTB FTL RPL13 ..." # Truncated for example purposes
+cell_sentence = "MALAT1 TMSB4X B2M EEF1A1 H3F3B ACTB FTL RPL13 ..." # Truncated for example, use at least 200 genes for inference
 num_genes = 1000
 organism = "Homo sapiens"
 
@@ -183,8 +191,7 @@ established best practices for splitting data to ensure robust and unbiased asse
 
 ## License
 
-The model weights are released under the Creative Commons Zero v1.0 Universal (CC0 1.0) license. 
-The underlying codebase for the Cell2Sentence project is licensed under CC BY-NC-ND 4.0.
+The model weights shared on Huggingface are CC-by-4.0.
 
 ## Implementation information
 
@@ -241,4 +248,4 @@ C2S-Scale provides a powerful, versatile, and scalable tool for single-cell anal
 # Gemma-2 Links
 - HuggingFace: https://huggingface.co/google/gemma-2-2b
 - Gemma-2 Blog Post: [Gemma explained: What's new in Gemma 2](https://developers.googleblog.com/en/gemma-explained-new-in-gemma-2/)
-- Technical report: https://storage.googleapis.com/deepmind-media/gemma/gemma-2-report.pdf
+- Technical report: https://storage.googleapis.com/deepmind-media/gemma/gemma-2-report.pdf