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LM Studio's own UI takes it from there.","prefilledFrom":{"file":"Nanbeige4.1-3B.Q4_K_M.gguf","templateSha256":"757f108242fb797d23b79f72c088cb5b4bc37fb3744e29dc8771c1dc2b1cb335","sha256":"0ba28f064c66071646e7959c752851abf02a096f1d37e7d0e443e3502e12ca02"},"guideCheckedAt":"2026-09-22","guideCheckedBy":"hugging-bay-docs","guideVersion":5},{"tool":"ollama","label":"Ollama","note":"Builds a local Ollama model named \"nanbeige4.1-3b.q4_k_m\" from the file (Ollama imports the file's embedded chat template) and starts a chat.","prefilledFrom":{"file":"Nanbeige4.1-3B.Q4_K_M.gguf","templateSha256":"757f108242fb797d23b79f72c088cb5b4bc37fb3744e29dc8771c1dc2b1cb335","sha256":"0ba28f064c66071646e7959c752851abf02a096f1d37e7d0e443e3502e12ca02"},"guideCheckedAt":"2026-09-22","guideCheckedBy":"hugging-bay-docs","guideVersion":5},{"tool":"llama.cpp","label":"llama.cpp (terminal)","kind":"terminal","proven":true,"note":"Runs the file directly with llama.cpp's command-line tool. -st (--single-turn) runs one turn with the model's embedded chat template and exits — tested on llama.cpp b10964-b29c606e2. The old -no-cnv flag was removed and is rejected by current builds.","runner":{"name":"llama.cpp","testedBuild":"b10964-b29c606e2","singleTurnFlag":"-st"},"prefilledFrom":{"file":"Nanbeige4.1-3B.Q4_K_M.gguf","templateSha256":"757f108242fb797d23b79f72c088cb5b4bc37fb3744e29dc8771c1dc2b1cb335","sha256":"0ba28f064c66071646e7959c752851abf02a096f1d37e7d0e443e3502e12ca02"},"guideCheckedAt":"2026-09-22","guideCheckedBy":"hugging-bay-docs","guideVersion":5},{"tool":"python","label":"Python (llama-cpp-python)","command":"pip install llama-cpp-python && python -c 'from llama_cpp import Llama; llm = Llama(\"./Nanbeige4.1-3B.Q4_K_M.gguf\", n_ctx=8192); print(llm.create_chat_completion(messages=[{'\\''role'\\'': '\\''user'\\'', '\\''content'\\'': '\\''Hello!'\\''}])['\\''choices'\\''][0]['\\''message'\\'']['\\''content'\\''])'","note":"For scripting the model from Python; create_chat_completion applies the embedded chat 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           {{- '<|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\": ' 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           {{- '<|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 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