{"id":143,"date":"2025-04-10T17:35:01","date_gmt":"2025-04-10T09:35:01","guid":{"rendered":"https:\/\/www.zhaozhao123.cn\/gongju\/?p=143"},"modified":"2025-04-10T17:35:42","modified_gmt":"2025-04-10T09:35:42","slug":"2025%e5%b9%b45%e4%b8%aa%e4%b8%bb%e6%b5%81%e5%bc%80%e6%ba%90%e4%b8%ad%e6%96%87%e5%af%b9%e8%af%9d%e5%bc%8fai%e6%a8%a1%e5%9e%8b%e6%b8%85%e5%8d%95%e5%8f%8a%e4%bd%bf%e7%94%a8%e8%af%b4%e6%98%8e","status":"publish","type":"post","link":"https:\/\/www.zhaozhao123.cn\/gongju\/post\/143.html","title":{"rendered":"2025\u5e745\u4e2a\u4e3b\u6d41\u5f00\u6e90\u4e2d\u6587\u5bf9\u8bdd\u5f0fAI\u6a21\u578b\u6e05\u5355\u53ca\u4f7f\u7528\u8bf4\u660e"},"content":{"rendered":"\n

\u4ee5\u4e0b\u662f\u622a\u81f32025\u5e745\u4e2a\u4e3b\u6d41\u5f00\u6e90\u4e2d\u6587\u5bf9\u8bdd\u5f0fAI\u6a21\u578b\u6e05\u5355\u53ca\u4f7f\u7528\u8bf4\u660e\uff0c\u7ed3\u5408\u6700\u65b0\u6280\u672f\u52a8\u6001\u6574\u7406\uff1a<\/p>\n\n\n\n

\n\n\n\n

\u4e00\u3001\u4e3b\u6d41\u5f00\u6e90\u6a21\u578b\u6e05\u5355<\/strong><\/h3>\n\n\n\n

1. DeepSeek-R1<\/strong><\/h4>\n\n\n\n
    \n
  • \u7279\u70b9<\/strong>\uff1a\u652f\u6301\u6570\u5b66\u63a8\u5bfc\/\u6587\u672c\u751f\u6210\u53cc\u6a21\u5f0f\uff0c\u54cd\u5e94\u5ef6\u8fdf<500ms<\/li>\n\n\n\n
  • \u90e8\u7f72\u65b9\u5f0f<\/strong>\uff1a<\/li>\n<\/ul>\n\n\n\n
      # \u901a\u8fc7API\u8c03\u7528\uff08\u9700\u7533\u8bf7\u5bc6\u94a5\uff09\n  from deepseek import DeepSeek\n  ds = DeepSeek(api_key=\"your_key\")\n  response = ds.chat(\"\u5982\u4f55\u8ba1\u7b97\u5706\u5468\u7387\uff1f\", model=\"r1-math\")<\/code><\/pre>\n\n\n\n
      \n
    • \u9002\u7528\u573a\u666f<\/strong>\uff1a\u6559\u80b2\u8f85\u5bfc\u3001\u79d1\u7814\u8ba1\u7b97<\/li>\n<\/ul>\n\n\n\n
      2. Qwen2.5-1M<\/strong><\/h4>\n\n\n\n
        \n
      • \u7a81\u7834<\/strong>\uff1a\u539f\u751f\u652f\u6301\u767e\u4e07Token\u4e0a\u4e0b\u6587\uff08\u5b9e\u6d4b\u53ef\u5904\u7406800\u9875PDF\uff09<\/li>\n\n\n\n
      • \u90e8\u7f72\u793a\u4f8b<\/strong>\uff1a<\/li>\n<\/ul>\n\n\n\n
          # HuggingFace\u5feb\u901f\u8c03\u7528\n  from transformers import AutoModelForCausalLM\n  model = AutoModelForCausalLM.from_pretrained(\"Qwen\/Qwen2.5-7B-Instruct-1M\")<\/code><\/pre>\n\n\n\n
        3. Llama3-Chinese-8B<\/strong><\/h4>\n\n\n\n
          \n
        • \u4f18\u52bf<\/strong>\uff1a\u4e13\u4e3a\u4e2d\u6587\u4f18\u5316\u7684Llama3\u5206\u652f\uff0c\u652f\u6301\u591a\u8f6e\u5bf9\u8bdd\u8bb0\u5fc6<\/li>\n\n\n\n
        • \u786c\u4ef6\u8981\u6c42<\/strong>\uff1aRTX 3090(24G)\u53ef\u6d41\u7545\u8fd0\u884c<\/li>\n\n\n\n
        • \u5fae\u8c03\u6307\u5357<\/strong>\uff1a<\/li>\n<\/ul>\n\n\n\n
            # \u4f7f\u7528LoRA\u5fae\u8c03\n  peft_config = LoraConfig(task_type=TaskType.CAUSAL_LM)\n  trainer = SFTTrainer(model, peft_config=peft_config, dataset=dataset)<\/code><\/pre>\n\n\n\n
          4. Ultravox v0.4.1<\/strong><\/h4>\n\n\n\n
            \n
          • \u521b\u65b0\u70b9<\/strong>\uff1a\u8de8\u6a21\u6001\u5bf9\u8bdd\uff08\u6587\u672c+\u56fe\u50cf\uff09\uff0c\u54cd\u5e94\u901f\u5ea6\u6bd4GPT-4\u5feb30%<\/li>\n\n\n\n
          • \u90e8\u7f72\u6d41\u7a0b<\/strong>\uff1a<\/li>\n<\/ul>\n\n\n\n
              # \u5b89\u88c5HuggingFace\u6269\u5c55\u5305\n  from ultravox import MultimodalPipeline\n  pipe = MultimodalPipeline.from_pretrained(\"fixie-ai\/ultravox-4.1\")<\/code><\/pre>\n\n\n\n
            5. \u58f0\u7f51\u5bf9\u8bdd\u5f0fAI\u5957\u4ef6<\/strong> [20-22]<\/h4>\n\n\n\n
              \n
            • \u7279\u8272<\/strong>\uff1a\u5f00\u6e90\u786c\u4ef6\u65b9\u6848\uff08BK7258\u82af\u7247\uff09+\u7aef\u4fa7\u5b9e\u65f6\u8bed\u97f3\u4ea4\u4e92<\/li>\n\n\n\n
            • \u5f00\u53d1\u6b65\u9aa4<\/strong>\uff1a<\/li>\n<\/ul>\n\n\n\n
                \n
              1. \u4e0b\u8f7d\u786c\u4ef6\u539f\u7406\u56fe\uff08GitHub\/Agora-Lab\uff09<\/li>\n\n\n\n
              2. \u70e7\u5f55\u9884\u7f16\u8bd1\u56fa\u4ef6<\/li>\n\n\n\n
              3. \u901a\u8fc7SDK\u96c6\u6210\u8bed\u97f3\u5524\u9192\u529f\u80fd<\/li>\n<\/ol>\n\n\n\n
                \n\n\n\n
                \u4e8c\u3001\u9009\u578b\u5bf9\u6bd4\u7ef4\u5ea6<\/strong><\/h3>\n\n\n\n
                \u6a21\u578b<\/th>\u591a\u8f6e\u5bf9\u8bdd<\/th>\u591a\u6a21\u6001<\/th>\u6700\u4f4e\u663e\u5b58<\/th>\u5546\u7528\u8bb8\u53ef<\/th><\/tr><\/thead>
                DeepSeek-R1<\/td>\u2714\ufe0f<\/td>\u274c<\/td>8GB<\/td>Apache 2.0<\/td><\/tr>
                Qwen2.5-1M<\/td>\u2714\ufe0f<\/td>\u2714\ufe0f<\/td>16GB<\/td>\u9700\u7533\u8bf7<\/td><\/tr>
                Llama3-Chinese<\/td>\u2714\ufe0f<\/td>\u274c<\/td>12GB<\/td>\u975e\u5546\u7528<\/td><\/tr>
                Ultravox<\/td>\u2714\ufe0f<\/td>\u2714\ufe0f<\/td>10GB<\/td>MIT<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
                \n\n\n\n
                \u4e09\u3001\u90e8\u7f72\u6ce8\u610f\u4e8b\u9879<\/strong><\/h3>\n\n\n\n
                  \n
                1. \u663e\u5b58\u4f18\u5316<\/strong>\uff1a\u5efa\u8bae\u4f7f\u7528\u91cf\u5316\u6280\u672f\uff08\u5982GPTQ\/GGUF\uff09\uff0c\u53ef\u5c06\u663e\u5b58\u9700\u6c42\u964d\u4f4e40%<\/li>\n\n\n\n
                2. \u6570\u636e\u5b89\u5168<\/strong>\uff1a\u672c\u5730\u90e8\u7f72\u65b9\u6848\u4f18\u5148\u9009\u62e9DB-GPT\u7b49\u652f\u6301\u79c1\u6709\u5316\u67b6\u6784\u7684\u6a21\u578b<\/li>\n\n\n\n
                3. \u6cd5\u5f8b\u5408\u89c4<\/strong>\uff1a\u6ce8\u610fLlama\u7cfb\u5217\u6a21\u578b\u7684\u975e\u5546\u7528\u9650\u5236\uff0c\u5546\u4e1a\u573a\u666f\u5efa\u8bae\u9009\u62e9ChatGLM\u6216\u81ea\u7814\u6a21\u578b<\/li>\n<\/ol>\n\n\n\n
                  \u5efa\u8bae\u901a\u8fc7\u5404\u9879\u76eeGitHub\u4ed3\u5e93\u83b7\u53d6\u6700\u65b0\u90e8\u7f72\u6307\u5357\uff08\u90e8\u5206\u6a21\u578b\u5468\u66f4\u65b0\u9891\u7387\uff09\uff0c\u9047\u5230\u6280\u672f\u95ee\u9898\u53ef\u4f18\u5148\u67e5\u9605\u9879\u76eeDiscussions\u677f\u5757\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
                  \u4ee5\u4e0b\u662f\u622a\u81f32025\u5e745\u4e2a\u4e3b\u6d41\u5f00\u6e90\u4e2d\u6587\u5bf9\u8bdd\u5f0fAI\u6a21\u578b\u6e05\u5355\u53ca\u4f7f\u7528\u8bf4\u660e\uff0c\u7ed3\u5408\u6700\u65b0\u6280\u672f\u52a8\u6001\u6574\u7406\uff1a \u4e00\u3001\u4e3b\u6d41\u5f00\u6e90\u6a21\u578b\u6e05\u5355 1. DeepSeek-R1 2. Qwen2.5-1M 3. Llama3-Chinese-8B 4. Ultravox v0.4.1 5. \u58f0\u7f51\u5bf9\u8bdd\u5f0fAI\u5957\u4ef6 [20-22] \u4e8c\u3001\u9009\u578b\u5bf9\u6bd4\u7ef4\u5ea6 \u6a21\u578b \u591a\u8f6e..<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[65],"tags":[],"tuisongtax":[],"class_list":["post-143","post","type-post","status-publish","format-standard","hentry","category-aixx"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.zhaozhao123.cn\/gongju\/wp-json\/wp\/v2\/posts\/143","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.zhaozhao123.cn\/gongju\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.zhaozhao123.cn\/gongju\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.zhaozhao123.cn\/gongju\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.zhaozhao123.cn\/gongju\/wp-json\/wp\/v2\/comments?post=143"}],"version-history":[{"count":0,"href":"https:\/\/www.zhaozhao123.cn\/gongju\/wp-json\/wp\/v2\/posts\/143\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.zhaozhao123.cn\/gongju\/wp-json\/wp\/v2\/media?parent=143"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.zhaozhao123.cn\/gongju\/wp-json\/wp\/v2\/categories?post=143"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.zhaozhao123.cn\/gongju\/wp-json\/wp\/v2\/tags?post=143"},{"taxonomy":"tuisongtax","embeddable":true,"href":"https:\/\/www.zhaozhao123.cn\/gongju\/wp-json\/wp\/v2\/tuisongtax?post=143"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}