Upload folder using huggingface_hub
Browse files- .gitattributes +2 -0
- README.md +15 -0
- config.json +10 -0
- embeddings_bf16.bin +3 -0
- export_args.json +42 -0
- llm.mnn +3 -0
- llm.mnn.json +0 -0
- llm.mnn.weight +3 -0
- llm_config.json +11 -0
- tokenizer.txt +0 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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llm.mnn filter=lfs diff=lfs merge=lfs -text
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llm.mnn.weight filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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language:
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- en
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base_model: Nanbeige/Nanbeige4.1-3B
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base_model_relation: quantized
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pipeline_tag: text-generation
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library_name: mnn
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tags:
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- code
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- mnn
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---
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This model [DeProgrammer/Nanbeige4.1-3B-MNN](https://huggingface.co/DeProgrammer/Nanbeige4.1-3B-MNN) was
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converted to MNN format from [Nanbeige/Nanbeige4.1-3B](https://huggingface.co/Nanbeige/Nanbeige4.1-3B)
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using [llmexport.py](https://github.com/alibaba/MNN/issues/4153#issuecomment-3866182869) in [MNN version **3.4.0**](https://github.com/alibaba/MNN/commit/a874b302f094599e2838a9186e5ce2cf6a81a7a7).
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Inference can be run via MNN, e.g., MNN Chat on Android.
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config.json
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{
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"llm_model": "llm.mnn",
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"llm_weight": "llm.mnn.weight",
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"backend_type": "cpu",
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"thread_num": 4,
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"precision": "low",
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"memory": "low",
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"sampler_type": "penalty",
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"penalty": 1.1
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}
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embeddings_bf16.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:038397ef5b03e16c16d8d69df3c03d503e3d279913dca86dacae53d8c182803a
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size 850657280
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export_args.json
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{
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"path": "Nanbeige/Nanbeige4.1-3B",
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"type": null,
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"tokenizer_path": "Nanbeige/Nanbeige4.1-3B",
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"eagle_path": null,
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"lora_path": null,
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"gptq_path": null,
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"dst_path": "./model",
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"verbose": false,
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"test": null,
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"export": "mnn",
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"onnx_slim": false,
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"quant_bit": 8,
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"quant_block": 64,
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"visual_quant_bit": null,
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"visual_quant_block": null,
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"lm_quant_bit": 8,
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"lm_quant_block": 64,
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"mnnconvert": "../../../build/MNNConvert",
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"ppl": false,
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"awq": false,
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"hqq": false,
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"omni": false,
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"transformer_fuse": false,
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"group_conv_native": false,
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"smooth": false,
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"sym": false,
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"visual_sym": false,
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"seperate_embed": false,
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"lora_split": false,
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"calib_data": null,
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"act_bit": 16,
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"embed_bit": 16,
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"act_sym": false,
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"quant_config": null,
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"generate_for_npu": false,
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"skip_weight": false,
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"omni_epochs": 20,
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"omni_lr": 0.005,
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"omni_wd": 0.0001,
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"tie_word_embeddings": false
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}
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llm.mnn
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version https://git-lfs.github.com/spec/v1
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oid sha256:d4e22b71abb1d44f17640d5a25a280595d966e66f818f2ff455e7a1a015e858e
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size 558736
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llm.mnn.json
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llm.mnn.weight
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version https://git-lfs.github.com/spec/v1
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oid sha256:3269e2db150a7a4e427513f16fa2a11a1e19707d1c2814c2b3bf1e27dbae60b9
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size 3948049994
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llm_config.json
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{
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"model_type": "llama",
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"hidden_size": 2560,
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"attention_mask": "float",
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"attention_type": "full",
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"jinja": {
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"chat_template": "\n {%- if tools %}\n {{- '<|im_start|>system\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\n\n' }}\n {%- else %} \n {{- '你是一位工具函数调用专家,你会得到一个问题和一组可能的工具函数。根据问题,你需要进行一个或多个函数/工具调用以实现目的,请尽量尝试探索通过工具解决问题。\n如果没有一个函数可以使用,请直接使用自然语言回复用户。\n如果给定的问题缺少函数所需的参数,请使用自然语言进行提问,向用户询问必要信息。\n如果调用结果已经足够回答用户问题,请对历史结果进行总结,使用自然语言回复用户。' }} \n {%- endif %}\n {{- \"# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\n</tool_call><|im_end|>\n\" }}\n {%- else %}\n {%- if messages[0].role == 'system' %}\n {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}\n {%- else %} \n {{- '<|im_start|>system\n你是南北阁,一款由BOSS直聘自主研发并训练的专业大语言模型。<|im_end|>\n' }} \n {%- endif %}\n {%- endif %}\n {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n {%- for message in messages[::-1] %}\n {%- set index = (messages|length - 1) - loop.index0 %}\n {%- if ns.multi_step_tool and message.role == \"user\" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n {%- endfor %}\n {%- for message in messages %}\n {%- if message.content is string %}\n {%- set content = message.content %}\n {%- else %}\n {%- set content = '' %}\n {%- endif %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}\n {%- elif message.role == \"assistant\" %}\n {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is string %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- else %}\n {%- if '</think>' in content %}\n {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}\n {%- set content = content.split('</think>')[-1].lstrip('\n') %}\n {%- endif %}\n {%- endif %}\n {%- if loop.index0 > ns.last_query_index or keep_all_think or (extra_body is defined and extra_body.keep_all_think) %}\n {%- if loop.last or (not loop.last and reasoning_content) %}\n {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\n' + content }}\n {%- endif %}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\n' + content }}\n {%- endif %}\n {%- if message.tool_calls %}\n {%- for tool_call in message.tool_calls %}\n {%- if (loop.first and content) or (not loop.first) %}\n {{- '\n' }}\n {%- endif %}\n {%- if tool_call.function %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '<tool_call>\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {%- if tool_call.arguments is string %}\n {{- tool_call.arguments }}\n {%- else %}\n {{- tool_call.arguments | tojson }}\n {%- endif %}\n {{- '}\n</tool_call>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\n<tool_response>\n' }}\n {{- content }}\n {{- '\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\n' }}\n {%- endif %}\n {%- endif %}\n {%- endfor %}\n {%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\n' }}\n {%- endif %}\n",
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"bos": "<|im_start|>",
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"eos": "<|im_end|>"
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}
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}
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tokenizer.txt
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