Update README.md

README.md

@@ -1,3 +1,71 @@
 ---
 license: apache-2.0
+tags:
+- function call
 ---
+XAgentLLaMa is a collection of fine-tuned generative text models ranging in scale from 7 billion to 34 billion based on Llama 2 and Code Llama.
+This is the repository for the 34B fine-tuned model, optimized for XAgent with strong function call ability.
+
+## Warning: This is a preview version of the model, does not stand for final quality.
+
+We collect around 300K pieces of data and fine-tune Code-Llama 34B with 48 A100 GPUs. More details will be released later.
+
+This model is trained with a special function call format, and should be used with [XAgentGen](https://github.com/OpenBMB/XAgent/tree/dev/XAgentGen) to get best performance.
+
+### XAgentGen input format:
+```json
+"messages":[
+    {
+    "role":"system",
+    "content":"...."
+    },
+    {...}
+],
+"global_arguments":{ // Optional
+    "type": "object",
+    "properties":{
+        "k1":{
+            "type":"integer",
+            "description":"..."
+        },
+        "k2":{
+            "type":"string",
+            "description":"..."
+        },
+        ...
+    },
+    "required":["k1","k2"]
+},
+"functions":[// Optional
+    {
+        "name":"func1",
+        "description":"...",
+        "parameters":{
+            "type":"object",
+            "properties":{...},
+            "required":[...]
+        }
+    },
+    ....
+],
+"function_call": {// Optional
+    "name":"func1"
+}
+```
+
+### XAgentGen call output format:
+```json
+{
+    "global_arguments": {
+        "k1":"v1",
+        "k2":"v2",
+        "k3":"v3",
+        ...
+    },
+    "function_call":{
+        "name":"func1",
+        "arguments":{...}
+    }
+}
+```
+If the json format of `global_arguments` is provided, the output will contains the `global_arguments` at any time.