修复直接读取Llama3，Qwen2的HF模型时的问题

src/model.cpp

@@ -402,13 +402,37 @@ namespace fastllm {
         for (auto &it : config.object_items()) {
             model->weight.AddDict(it.first, it.second.dump().c_str());
         }
+        // 设置eos_token_id
+        if (config["eos_token_id"].is_array()) {
+            for (auto &it : config["eos_token_id"].array_items()) {
+                model->eos_token_ids.insert(it.int_value());
+            }
+        } else {
+            model->eos_token_id = config["eos_token_id"].int_value();
+        }
+
+        std::string generatetionConfigFile = path + "generation_config.json";
+        if (FileExists(generatetionConfigFile)) {
+            auto generation_config = json11::Json::parse(ReadAllFile(generatetionConfigFile), error);
+            for (auto &it : generation_config.object_items()) {
+                if ("eos_token_id" == it.first && it.second.type() == json11::Json::ARRAY)
+                    continue;
+                model->weight.AddDict(it.first, it.second.dump().c_str());
+            }
+            // 更新eos_token_id
+            if (generation_config["eos_token_id"].is_array()) {
+                for (auto &it : generation_config["eos_token_id"].array_items()) {
+                    model->eos_token_ids.insert(it.int_value());
+                }
+            }
+        }
 
         // 3. 读取分词
         std::string tokenizerConfigFile = path + "tokenizer_config.json";
         auto tokenizerConfig = json11::Json::parse(ReadAllFile(tokenizerConfigFile), error);
         model->weight.tokenizer.SetTokenizerConfig(tokenizerConfig);
         std::string tokenizerClass = tokenizerConfig["tokenizer_class"].string_value();
-        if (tokenizerClass == "PreTrainedTokenizerFast") {
+        if (tokenizerClass == "PreTrainedTokenizerFast" || tokenizerClass == "Qwen2Tokenizer") {
             // PreTrainedTokenizerFast
             std::string tokenizerFile = path + "tokenizer.json";
             auto tokenizer = json11::Json::parse(ReadAllFile(tokenizerFile), error);
@@ -445,15 +469,6 @@ namespace fastllm {
             ((ChatGLMModel*)model)->bos_token_id = model->weight.tokenizer.GetTokenId("<sop>");
             ((ChatGLMModel*)model)->tokenizerClass = tokenizerClass;
 
-            // 设置eos_token_id
-            if (config["eos_token_id"].is_array()) {
-                for (auto &it : config["eos_token_id"].array_items()) {
-                    model->eos_token_ids.insert(it.int_value());
-                }
-            } else {
-                model->eos_token_id = config["eos_token_id"].int_value();
-            }
-
             // ChatGLM采用拼接token的方法，需要强行指定分割词的TokenID
             model->pre_prompt = "";
             model->user_role = ("<FLM_FIX_TOKEN_" + std::to_string(model->weight.tokenizer.GetTokenId("<|user|>"))  + ">\n");

src/models/basellm.cpp

@@ -984,6 +984,7 @@ printf("len = %d, spend = %f s. tokens / s = %f\n", (int)total, spend, (float)to
                 {"content", message.second}
             });
         }
+        ret["add_generation_prompt"] = fastllm::JinjaVar{1};
         return ret;
     }
 

src/models/llama.cpp

@@ -926,6 +926,10 @@ namespace fastllm {
             pastKeyValues.push_back(std::make_pair(Data(DataType::FLOAT32),
                                                    Data(DataType::FLOAT32)));
         }
+        if (this->weight.weight.find("lm_head.weight") == this->weight.weight.end()) {
+            this->weight["lm_head.weight"] = Data();
+            this->weight["lm_head.weight"].CopyFrom(this->weight["model.embed_tokens.weight"]);
+        }
         Forward(inputIds, attentionMask, positionIds, pastKeyValues);
         printf("finish.\n");
     }