Instructions to use yujiepan/minimax-m1-tiny-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yujiepan/minimax-m1-tiny-random with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="yujiepan/minimax-m1-tiny-random", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("yujiepan/minimax-m1-tiny-random", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use yujiepan/minimax-m1-tiny-random with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "yujiepan/minimax-m1-tiny-random" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yujiepan/minimax-m1-tiny-random", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/yujiepan/minimax-m1-tiny-random
- SGLang
How to use yujiepan/minimax-m1-tiny-random 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 "yujiepan/minimax-m1-tiny-random" \ --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": "yujiepan/minimax-m1-tiny-random", "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 "yujiepan/minimax-m1-tiny-random" \ --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": "yujiepan/minimax-m1-tiny-random", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use yujiepan/minimax-m1-tiny-random with Docker Model Runner:
docker model run hf.co/yujiepan/minimax-m1-tiny-random
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| "add_prefix_space": false, | |
| "added_tokens_decoder": { | |
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| "bos_token": "<beginning_of_sentence>", | |
| "chat_template": "{{ '<begin_of_document>' -}}{% set ns = namespace(system_prompt='') -%}{% for message in messages -%}{% if message['role'] == 'system' -%}{% set ns.system_prompt = ns.system_prompt + message['content'][0]['text'] -%}{% endif -%}{%- endfor -%}{% if ns.system_prompt != '' -%}{{ '<beginning_of_sentence>system ai_setting=assistant\n' + ns.system_prompt + '<end_of_sentence>\n' -}}{%- endif -%}{% if tools -%}{{ '<beginning_of_sentence>system tool_setting=tools\nYou are provided with these tools:\n<tools>\n' -}}{% for tool in tools -%}{{ tool | tojson ~ '\n' -}}{%- endfor -%}{{ '</tools>\n\nIf you need to call tools, please respond with <tool_calls></tool_calls> XML tags, and provide tool-name and json-object of arguments, following the format below:\n<tool_calls>\n{''name'': <tool-name-1>, ''arguments'': <args-json-object-1>}\n...\n</tool_calls><end_of_sentence>\n' -}}{%- endif -%}{% for message in messages -%}{% if message['role'] == 'user' -%}{{ '<beginning_of_sentence>user name=user\n' + message['content'][0]['text'] + '<end_of_sentence>\n' -}}{% elif message['role'] == 'assistant' -%}{{ '<beginning_of_sentence>ai name=assistant\n' -}}{% for content in message['content'] | selectattr('type', 'equalto', 'text') -%}{{ content['text'] -}}{%- endfor -%}{{ '<end_of_sentence>\n' -}}{% elif message['role'] == 'tool' -%}{{ '<beginning_of_sentence>tool name=tools\n' }} {%- for content in message['content'] -%}{{- 'tool name: ' + content['name'] + '\n' + 'tool result: ' + content['text'] + '\n\n' -}} {%- endfor -%}{{- '<end_of_sentence>\n' -}}{% endif -%}{%- endfor -%}{% if add_generation_prompt -%}{{ '<beginning_of_sentence>ai name=assistant\n' -}}{%- endif -%}", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<end_of_sentence>", | |
| "extra_special_tokens": {}, | |
| "model_max_length": 40960000, | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": "<end_of_document>" | |
| } | |