Add library name and link to code

This PR makes sure that people can more easily find the Github repository and that the appropriate "how to use" button shows up.

README.md

@@ -1,11 +1,13 @@
 ---
-license: cc-by-nc-4.0
+datasets:
+- zjunlp/ChineseHarm-bench
 language:
 - zh
+license: cc-by-nc-4.0
 pipeline_tag: text-classification
-datasets:
-- zjunlp/ChineseHarm-bench
+library_name: transformers
 ---
+
 ## 🚀Installation
 
 1. Clone the repositories:
@@ -27,13 +29,17 @@ datasets:
 
 We release the following variants of our harmful content detection model:
 
+- [**ChineseGuard-1.5B**](https://huggingface.co/zjunlp/ChineseGuard-1.5B)
+- [**ChineseGuard-3B**](https://huggingface.co/zjunlp/ChineseGuard-3B)
+- [**ChineseGuard-7B**](https://huggingface.co/zjunlp/ChineseGuard-7B)
+
 🔹 Single Inference (Example)
 
-Run single-input inference using the ChineseGuard-3B model:
+Run single-input inference using the ChineseGuard-1.5B model:
 
 ```
 SCRIPT_PATH="../infer/single_infer.py"
-model_name="zjunlp/ChineseGuard-3B"
+model_name="zjunlp/ChineseGuard-1.5B"
 text="代发短信，有想做的联系我，无押金"
 
 python $SCRIPT_PATH \
@@ -43,13 +49,13 @@ python $SCRIPT_PATH \
 
 🔸 Batch Inference (Multi-NPU or Multi-GPU)
 
-To run inference on the entire ChineseHarm-Bench using ChineseGuard-3B and 8 NPUs:
+To run inference on the entire ChineseHarm-Bench using ChineseGuard-1.5B and 8 NPUs:
 
 ```
 SCRIPT_PATH="../infer/batch_infer.py"
-model_name="zjunlp/ChineseHarm-3B"
+model_name="zjunlp/ChineseHarm-1.5B"
 file_name="../benchmark/bench.json"
-output_file="../benchmark/bench_ChineseHarm-3B.json"
+output_file="../benchmark/bench_ChineseHarm-1.5B.json"
 
 python $SCRIPT_PATH \
     --model_name $model_name \
@@ -63,9 +69,20 @@ python $SCRIPT_PATH \
 >
 > **Note:** The inference scripts support both NPU and GPU devices.
 
+**Evaluation: Calculating F1 Score**
+
+After inference, evaluate the predictions by computing the F1 score with the following command:
+
+```
+python ../calculate_metrics.py \
+    --file_path "../benchmark/bench_ChineseHarm-1.5B.json" \
+    --true_label_field "标签" \
+    --predicted_label_field "predict_label"
+```
+
 ## 🚩Citation
 
-Please cite our repository if you use ChineseGuard in your work. Thanks!
+Please cite our repository if you use ChineseHarm-bench in your work. Thanks!
 
 ```bibtex
 @misc{liu2025chineseharmbenchchineseharmfulcontent,
@@ -77,4 +94,6 @@ Please cite our repository if you use ChineseGuard in your work. Thanks!
       primaryClass={cs.CL},
       url={https://arxiv.org/abs/2506.10960}, 
 }
-```
+```
+
+Codebase: https://github.com/zjunlp/ChineseHarm-bench