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- .gitattributes +1 -0
- README.md +57 -0
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        .gitattributes
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        README.md
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            ---
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            language:
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            - en
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            - zh
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            library_name: transformers
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            license: mit
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            pipeline_tag: text-generation
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            +
            ---
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             | 
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            # GLM-4.6-FP8
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             | 
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            <div align="center">
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            <img src=https://raw.githubusercontent.com/zai-org/GLM-4.5/refs/heads/main/resources/logo.svg width="15%"/>
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            </div>
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            <p align="center">
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                👋 Join our <a href="https://discord.gg/QR7SARHRxK" target="_blank">Discord</a> community.
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                <br>
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                📖 Check out the GLM-4.6 <a href="https://z.ai/blog/glm-4.6" target="_blank">technical blog</a>, <a href="https://arxiv.org/abs/2508.06471" target="_blank">technical report(GLM-4.5)</a>, and <a href="https://zhipu-ai.feishu.cn/wiki/Gv3swM0Yci7w7Zke9E0crhU7n7D" target="_blank">Zhipu AI technical documentation</a>.
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                <br>
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                📍 Use GLM-4.6 API services on <a href="https://docs.z.ai/guides/llm/glm-4.6">Z.ai API Platform. </a>
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                <br>
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                👉 One click to <a href="https://chat.z.ai">GLM-4.6</a>.
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            </p>
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             | 
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            ## Model Introduction
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            Compared with GLM-4.5, **GLM-4.6**  brings several key improvements:
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            * **Longer context window:** The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex agentic tasks.
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            * **Superior coding performance:** The model achieves higher scores on code benchmarks and demonstrates better real-world performance in applications such as Claude Code、Cline、Roo Code and Kilo Code, including improvements in generating visually polished front-end pages.
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            * **Advanced reasoning:** GLM-4.6 shows a clear improvement in reasoning performance and supports tool use during inference, leading to stronger overall capability.
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            * **More capable agents:** GLM-4.6 exhibits stronger performance in tool using and search-based agents, and integrates more effectively within agent frameworks.
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            * **Refined writing:** Better aligns with human preferences in style and readability, and performs more naturally in role-playing scenarios.
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            We evaluated GLM-4.6 across eight public benchmarks covering agents, reasoning, and coding. Results show clear gains over GLM-4.5, with GLM-4.6 also holding competitive advantages over leading domestic and international models such as **DeepSeek-V3.1-Terminus** and **Claude Sonnet 4**.
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            ## Inference
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            **Both GLM-4.5 and GLM-4.6 use the same inference method.**
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             | 
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            you can check our [github](https://github.com/zai-org/GLM-4.5) for more detail.
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             | 
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            ## Recommended Evaluation Parameters
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            For general evaluations, we recommend using a **sampling temperature of 1.0**.
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            For **code-related evaluation tasks** (such as LCB), it is further recommended to set:
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             | 
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            - `top_p = 0.95`
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            - `top_k = 40`
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             | 
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            ## Evaluation
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             | 
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            - For tool-integrated reasoning, please refer to [this doc](https://github.com/zai-org/GLM-4.5/blob/main/resources/glm_4.6_tir_guide.md).
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            - For search benchmark, we design a specific format for searching toolcall in thinking mode to support search agent, please refer to [this](https://github.com/zai-org/GLM-4.5/blob/main/resources/trajectory_search.json). for the detailed template.
         | 
    	
        chat_template.jinja
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            [gMASK]<sop>
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            {%- if tools -%}
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            <|system|>
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            # Tools
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            You may call one or more functions to assist with the user query.
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            You are provided with function signatures within <tools></tools> XML tags:
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            <tools>
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            {% for tool in tools %}
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            {{ tool | tojson(ensure_ascii=False) }}
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            {% endfor %}
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            </tools>
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             | 
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            For each function call, output the function name and arguments within the following XML format:
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            <tool_call>{function-name}
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            <arg_key>{arg-key-1}</arg_key>
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            <arg_value>{arg-value-1}</arg_value>
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            <arg_key>{arg-key-2}</arg_key>
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            <arg_value>{arg-value-2}</arg_value>
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            ...
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            </tool_call>{%- endif -%}
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            {%- macro visible_text(content) -%}
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                {%- if content is string -%}
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                    {{- content }}
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                {%- elif content is iterable and content is not mapping -%}
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                    {%- for item in content -%}
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                        {%- if item is mapping and item.type == 'text' -%}
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                            {{- item.text }}
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                        {%- elif item is string -%}
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                            {{- item }}
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                        {%- endif -%}
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                    {%- endfor -%}
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                {%- else -%}
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                    {{- content }}
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                {%- endif -%}
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            {%- endmacro -%}
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            {%- set ns = namespace(last_user_index=-1) %}
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            {%- for m in messages %}
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                {%- if m.role == 'user' %}
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                    {% set ns.last_user_index = loop.index0 -%}
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                {%- endif %}
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            {%- endfor %}
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            {% for m in messages %}
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            {%- if m.role == 'user' -%}<|user|>
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            {{ visible_text(m.content) }}
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            {{- '/nothink' if (enable_thinking is defined and not enable_thinking and not visible_text(m.content).endswith("/nothink")) else '' -}}
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            {%- elif m.role == 'assistant' -%}
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            <|assistant|>
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            {%- set reasoning_content = '' %}
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            {%- set content = visible_text(m.content) %}
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            {%- if m.reasoning_content is string %}
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                {%- set reasoning_content = m.reasoning_content %}
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            {%- else %}
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                {%- if '</think>' in content %}
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                    {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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                    {%- set content = content.split('</think>')[-1].lstrip('\n') %}
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                {%- endif %}
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            {%- endif %}
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            {%- if loop.index0 > ns.last_user_index and reasoning_content -%}
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            {{ '\n<think>' + reasoning_content.strip() +  '</think>'}}
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            {%- else -%}
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            {{ '\n<think></think>' }}
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            {%- endif -%}
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            {%- if content.strip() -%}
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            {{ '\n' + content.strip() }}
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            {%- endif -%}
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            {% if m.tool_calls %}
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            {% for tc in m.tool_calls %}
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            {%- if tc.function %}
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                {%- set tc = tc.function %}
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            {%- endif %}
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            {{ '\n<tool_call>' + tc.name }}
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            {% set _args = tc.arguments %}
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            {% for k, v in _args.items() %}
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            <arg_key>{{ k }}</arg_key>
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            <arg_value>{{ v | tojson(ensure_ascii=False) if v is not string else v }}</arg_value>
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            {% endfor %}
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            +
            </tool_call>{% endfor %}
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| 80 | 
            +
            {% endif %}
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| 81 | 
            +
            {%- elif m.role == 'tool' -%}
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            +
            {%- if m.content is string -%}
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| 83 | 
            +
            {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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| 84 | 
            +
                {{- '<|observation|>' }}
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| 85 | 
            +
            {%- endif %}
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| 86 | 
            +
            {{- '\n<tool_response>\n' }}
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| 87 | 
            +
            {{- m.content }}
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| 88 | 
            +
            {{- '\n</tool_response>' }}
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| 89 | 
            +
            {%- else -%}
         | 
| 90 | 
            +
            <|observation|>{% for tr in m.content %}
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| 91 | 
            +
             | 
| 92 | 
            +
            <tool_response>
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| 93 | 
            +
            {{ tr.output if tr.output is defined else tr }}
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| 94 | 
            +
            </tool_response>{% endfor -%}
         | 
| 95 | 
            +
            {% endif -%}
         | 
| 96 | 
            +
            {%- elif m.role == 'system' -%}
         | 
| 97 | 
            +
            <|system|>
         | 
| 98 | 
            +
            {{ visible_text(m.content) }}
         | 
| 99 | 
            +
            {%- endif -%}
         | 
| 100 | 
            +
            {%- endfor -%}
         | 
| 101 | 
            +
            {%- if add_generation_prompt -%}
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| 102 | 
            +
                <|assistant|>{{- '\n<think></think>' if (enable_thinking is defined and not enable_thinking) else '' -}}
         | 
| 103 | 
            +
            {%- endif -%}
         | 
    	
        config.json
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            {
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              "architectures": [
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            +
                "Glm4MoeForCausalLM"
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            +
              ],
         | 
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            +
              "attention_bias": true,
         | 
| 6 | 
            +
              "attention_dropout": 0.0,
         | 
| 7 | 
            +
              "eos_token_id": [
         | 
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            +
                151329,
         | 
| 9 | 
            +
                151336,
         | 
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            +
                151338
         | 
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            +
              ],
         | 
| 12 | 
            +
              "first_k_dense_replace": 3,
         | 
| 13 | 
            +
              "head_dim": 128,
         | 
| 14 | 
            +
              "hidden_act": "silu",
         | 
| 15 | 
            +
              "hidden_size": 5120,
         | 
| 16 | 
            +
              "initializer_range": 0.02,
         | 
| 17 | 
            +
              "intermediate_size": 12288,
         | 
| 18 | 
            +
              "max_position_embeddings": 202752,
         | 
| 19 | 
            +
              "model_type": "glm4_moe",
         | 
| 20 | 
            +
              "moe_intermediate_size": 1536,
         | 
| 21 | 
            +
              "n_group": 1,
         | 
| 22 | 
            +
              "n_routed_experts": 160,
         | 
| 23 | 
            +
              "n_shared_experts": 1,
         | 
| 24 | 
            +
              "norm_topk_prob": true,
         | 
| 25 | 
            +
              "num_attention_heads": 96,
         | 
| 26 | 
            +
              "num_experts_per_tok": 8,
         | 
| 27 | 
            +
              "num_hidden_layers": 92,
         | 
| 28 | 
            +
              "num_key_value_heads": 8,
         | 
| 29 | 
            +
              "num_nextn_predict_layers": 1,
         | 
| 30 | 
            +
              "pad_token_id": 151329,
         | 
| 31 | 
            +
              "partial_rotary_factor": 0.5,
         | 
| 32 | 
            +
              "rms_norm_eps": 1e-05,
         | 
| 33 | 
            +
              "rope_scaling": null,
         | 
| 34 | 
            +
              "rope_theta": 1000000,
         | 
| 35 | 
            +
              "routed_scaling_factor": 2.5,
         | 
| 36 | 
            +
              "tie_word_embeddings": false,
         | 
| 37 | 
            +
              "topk_group": 1,
         | 
| 38 | 
            +
              "torch_dtype": "bfloat16",
         | 
| 39 | 
            +
              "transformers_version": "4.54.0",
         | 
| 40 | 
            +
              "use_cache": true,
         | 
| 41 | 
            +
              "use_qk_norm": true,
         | 
| 42 | 
            +
              "vocab_size": 151552
         | 
| 43 | 
            +
            }
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        generation_config.json
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