Text Generation
Transformers
Safetensors
iquestcoder
code
industrial-code
long-context
conversational
custom_code
Instructions to use Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4
- SGLang
How to use Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4 with Docker Model Runner:
docker model run hf.co/Multilingual-Multimodal-NLP/IndustrialCoder-32B-AWQ-INT4
| {%- if tools %} | |
| {{- '<|im_start|>system\n' }} | |
| {%- if messages[0].role == 'system' %} | |
| {{- messages[0].content + '\n\n' }} | |
| {%- else %} | |
| {{- 'You are IndustrialCoder, a helpful assistant developed by Beihang University.' }} | |
| {%- endif %} | |
| {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }} | |
| {%- for tool in tools %} | |
| {%- if tool.type == 'function' and tool.function %} | |
| {%- set func = tool.function %} | |
| {%- else %} | |
| {%- set func = tool %} | |
| {%- endif %} | |
| {{- "\n<function>\n<name>" + func.name + "</name>" }} | |
| {%- if func.description %} | |
| {{- "\n<description>" + func.description + "</description>" }} | |
| {%- endif %} | |
| {{- "\n<parameters>" }} | |
| {%- if func.parameters and func.parameters.properties %} | |
| {%- for param_name, param_fields in func.parameters.properties.items() %} | |
| {{- "\n<parameter>" }} | |
| {{- "\n<name>" + param_name + "</name>" }} | |
| {%- if param_fields.type %} | |
| {{- "\n<type>" + param_fields.type + "</type>" }} | |
| {%- endif %} | |
| {%- if param_fields.description %} | |
| {{- "\n<description>" + param_fields.description + "</description>" }} | |
| {%- endif %} | |
| {{- "\n</parameter>" }} | |
| {%- endfor %} | |
| {%- endif %} | |
| {{- "\n</parameters>\n</function>" }} | |
| {%- endfor %} | |
| {{- "\n</tools>\n\nIf you choose to call a function ONLY reply in the following format:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n</function>\n</tool_call><|im_end|>\n" }} | |
| {%- else %} | |
| {%- if messages[0].role == 'system' %} | |
| {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }} | |
| {%- else %} | |
| {{- '<|im_start|>system\nYou are IndustrialCoder, a helpful assistant developed by Beihang University.<|im_end|>\n' }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %} | |
| {%- for message in messages[::-1] %} | |
| {%- set index = (messages|length - 1) - loop.index0 %} | |
| {%- if ns.multi_step_tool and message.role == "user" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %} | |
| {%- set ns.multi_step_tool = false %} | |
| {%- set ns.last_query_index = index %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- for message in messages %} | |
| {%- if (message.role == "user") or (message.role == "system" and not loop.first) %} | |
| {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }} | |
| {%- elif message.role == "assistant" %} | |
| {%- set content = message.content %} | |
| {{- '<|im_start|>' + message.role + '\n' + content }} | |
| {%- if message.tool_calls %} | |
| {%- for tool_call in message.tool_calls %} | |
| {%- if (loop.first and content) or (not loop.first) %} | |
| {{- '\n' }} | |
| {%- endif %} | |
| {%- if tool_call.function %} | |
| {%- set tc = tool_call.function %} | |
| {%- else %} | |
| {%- set tc = tool_call %} | |
| {%- endif %} | |
| {{- '<tool_call>\n<function=' + tc.name + '>\n' }} | |
| {%- if tc.arguments is string %} | |
| {%- set args = tc.arguments | fromjson %} | |
| {%- else %} | |
| {%- set args = tc.arguments %} | |
| {%- endif %} | |
| {%- for arg_name, arg_value in args.items() %} | |
| {{- '<parameter=' + arg_name + '>\n' }} | |
| {%- if arg_value is string %} | |
| {{- arg_value }} | |
| {%- else %} | |
| {{- arg_value | tojson }} | |
| {%- endif %} | |
| {{- '\n</parameter>\n' }} | |
| {%- endfor %} | |
| {{- '</function>\n</tool_call>' }} | |
| {%- endfor %} | |
| {%- endif %} | |
| {{- '<|im_end|>\n' }} | |
| {%- elif message.role == "tool" %} | |
| {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %} | |
| {{- '<|im_start|>user' }} | |
| {%- endif %} | |
| {{- '\n<tool_response>\n' }} | |
| {{- message.content }} | |
| {{- '\n</tool_response>' }} | |
| {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %} | |
| {{- '<|im_end|>\n' }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- if add_generation_prompt %} | |
| {{- '<|im_start|>assistant\n' }} | |
| {%- endif %} |