Update README.md (#1)

- Update README.md (ccb4400a92178c3644ea4b98029e6e6c877551fa)

README.md

@@ -1,12 +1,23 @@
 ---
 library_name: transformers
-tags: []
+license: cc-by-sa-4.0
+language:
+- en
+- ja
+base_model:
+- EQUES/JPharmatron-7B-base
+tags:
+- pharmacy
+- biology
+- chemistry
+- medical
 ---
 
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
 
+JPharmatron-7B is a 7B large language model designed for pharmaceutical applications and researches.
 
 
 ## Model Details
@@ -15,23 +26,21 @@ tags: []
 
 <!-- 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.
+The JPharmatron-7B is continually pre-trained using 10T tokens from Japanese and English datasets, based on Qwen2.5-7B. Compared to the JPharmatron-7B-base model, JPharmatron-7B has enhanced chat capabilities, obtained from Qwen2.5-7B-Instruct's chat vector.
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- **Developed by:** EQUES Inc.
+- **Funded by [optional]:** [GENIAC Project](https://www.meti.go.jp/policy/mono_info_service/geniac/index.html)
+- **Model type:** Causal decoder-only
+- **Language(s) (NLP):** Japanese, English
+- **License:** CC-BY-SA-4.0
+- **Finetuned from model [optional]:** JPharmatron-7B-base
 
 ### Model Sources [optional]
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** https://github.com/EQUES-Inc/pharma-LLM-eval
+- **Paper [optional]:** [A Japanese Language Model and Three New Evaluation Benchmarks for Pharmaceutical NLP](https://arxiv.org/abs/2505.16661)
 
 ## Uses