Instructions to use tiny-random/hy3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiny-random/hy3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tiny-random/hy3") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("tiny-random/hy3") model = AutoModelForCausalLM.from_pretrained("tiny-random/hy3") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use tiny-random/hy3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tiny-random/hy3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tiny-random/hy3", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/tiny-random/hy3
- SGLang
How to use tiny-random/hy3 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 "tiny-random/hy3" \ --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": "tiny-random/hy3", "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 "tiny-random/hy3" \ --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": "tiny-random/hy3", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use tiny-random/hy3 with Docker Model Runner:
docker model run hf.co/tiny-random/hy3
| {#- ----------‑‑‑ special token variables ‑‑‑---------- -#} | |
| {%- set bos_token = '<|hy_begin▁of▁sentence|>' %} | |
| {%- set pad_token = '<|hy_▁pad▁|>' %} | |
| {%- set user_token = '<|hy_User|>' %} | |
| {%- set assistant_token = '<|hy_Assistant|>' %} | |
| {%- set eos_token = '<|hy_eos|>' %} | |
| {%- set think_begin_token = '<think>' %} | |
| {%- set think_end_token = '</think>' %} | |
| {%- set toolcalls_begin_token = '<tool_calls>' %} | |
| {%- set toolcalls_end_token = '</tool_calls>' %} | |
| {%- set toolcall_begin_token = '<tool_call>' %} | |
| {%- set toolcall_end_token = '</tool_call>' %} | |
| {%- set toolsep_token = '<tool_sep>' %} | |
| {%- set argkey_begin_token = '<arg_key>' %} | |
| {%- set argkey_end_token = '</arg_key>' %} | |
| {%- set argvalue_begin_token = '<arg_value>' %} | |
| {%- set argvalue_end_token = '</arg_value>' %} | |
| {%- set toolresponses_begin_token = '<tool_responses>' %} | |
| {%- set toolresponses_end_token = '</tool_responses>' %} | |
| {%- set toolresponse_begin_token = '<tool_response>' %} | |
| {%- set toolresponse_end_token = '</tool_response>' %} | |
| {%- set reasoning_mode_token = '<|reasoning_mode|>' %} | |
| {#- ----------‑‑‑ hyperparameters variables ‑‑‑---------- -#} | |
| {%- if not add_generation_prompt is defined %} | |
| {%- set add_generation_prompt = false %} | |
| {%- endif %} | |
| {%- if not interleaved_thinking is defined %} | |
| {%- set interleaved_thinking = false %} | |
| {%- endif %} | |
| {%- if not tools %} | |
| {%- set interleaved_thinking = false %} | |
| {%- endif %} | |
| {%- if not is_training is defined %} | |
| {%- set is_training = false %} | |
| {%- endif %} | |
| {%- if not reasoning_effort is defined or reasoning_effort not in ['high', 'low', 'no_think'] %} | |
| {%- set reasoning_effort = 'no_think' %} | |
| {%- endif %} | |
| {%- macro visible_text(content) -%} | |
| {%- if content is string -%} | |
| {{- content }} | |
| {%- elif content is iterable and content is not mapping -%} | |
| {%- for item in content -%} | |
| {%- if item is mapping and item.type == 'text' -%} | |
| {{- item.text }} | |
| {%- elif item is string -%} | |
| {{- item }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- elif content is none -%} | |
| {{- '' }} | |
| {%- else -%} | |
| {{- content }} | |
| {%- endif -%} | |
| {%- endmacro -%} | |
| {%- set ns = namespace(last_user_index=-1) %} | |
| {%- set sp_ns = namespace(system_prompt='', is_first_sp=true) %} | |
| {%- for message in messages %} | |
| {%- if message['role'] == 'system' %} | |
| {%- set sp_ns.system_prompt = sp_ns.system_prompt + visible_text(message['content']) %} | |
| {%- endif %} | |
| {%- if message['role'] == 'user' %} | |
| {%- set ns.last_user_index = loop.index0 %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- if reasoning_effort is defined and reasoning_effort is string and reasoning_effort != '' and not tools %} | |
| {%- set sp_ns.system_prompt = sp_ns.system_prompt + reasoning_mode_token + 'reasoning_effort:' + reasoning_effort %} | |
| {%- endif %} | |
| {{- bos_token }} | |
| {{- sp_ns.system_prompt }} | |
| {%- if tools %} | |
| {%- if sp_ns.system_prompt != '' %} | |
| {{- '\n\n# Tools\n\nYou may call one or more functions to assist with the user query.' }} | |
| {%- else %} | |
| {{- '# Tools\n\nYou may call one or more functions to assist with the user query.' }} | |
| {%- endif %} | |
| {{- '\n\nYou are provided with function signatures within <tools></tools> XML tags:' }} | |
| {{- '\n<tools>\n' }} | |
| {%- for tool in tools %} | |
| {%- if loop.index0 > 0 %} | |
| {{- '\n' }} | |
| {%- endif %} | |
| {{- tool | tojson }} | |
| {%- endfor %} | |
| {{- '\n</tools>\n\n' }} | |
| {{- 'For function call returns, you should first print ' + toolcalls_begin_token + '\n' }} | |
| {{- 'For each function call, you should return object like:\n' }} | |
| {{- toolcall_begin_token + '{function-name}' + toolsep_token + '\n' }} | |
| {{- argkey_begin_token + '{arg-key-1}' + argkey_end_token + '\n' }} | |
| {{- argvalue_begin_token + '{arg-value-1}' + argvalue_end_token + '\n' }} | |
| {{- argkey_begin_token + '{arg-key-2}' + argkey_end_token + '\n' }} | |
| {{- argvalue_begin_token + '{arg-value-2}' + argvalue_end_token + '\n' }} | |
| {{- '...\n' }} | |
| {{- toolcall_end_token + '\n' }} | |
| {%- if reasoning_effort is defined and reasoning_effort is string and reasoning_effort != '' %} | |
| {{- 'At the end of function call returns, you should print ' + toolcalls_end_token + reasoning_mode_token + 'reasoning_effort:' + reasoning_effort }} | |
| {%- else %} | |
| {{- 'At the end of function call returns, you should print ' + toolcalls_end_token }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- set prev_ns = namespace(is_tool=false, is_tool_first=true) %} | |
| {%- set last_ns = namespace(last_is_assistant=false) %} | |
| {%- for message in messages %} | |
| {%- if message['role'] == 'user' %} | |
| {%- if prev_ns.is_tool %} | |
| {{- toolresponses_end_token }} | |
| {%- endif %} | |
| {{- user_token + visible_text(message['content']) }} | |
| {%- set prev_ns.is_tool = false %} | |
| {%- endif %} | |
| {%- if message['role'] == 'assistant' %} | |
| {%- if 'reasoning_content' in message and message['reasoning_content'] is string %} | |
| {%- set rc = message['reasoning_content'] %} | |
| {%- elif 'reasoning' in message and message['reasoning'] is string %} | |
| {%- set rc = message['reasoning'] %} | |
| {%- else %} | |
| {%- set rc = none %} | |
| {%- endif %} | |
| {%- if is_training %} | |
| {%- if rc is not none %} | |
| {%- set content = think_begin_token + rc + think_end_token + visible_text(message['content']) %} | |
| {%- else %} | |
| {%- set content = think_begin_token + think_end_token + visible_text(message['content']) %} | |
| {%- endif %} | |
| {%- else %} | |
| {%- if interleaved_thinking %} | |
| {%- if loop.index0 > ns.last_user_index and rc is not none %} | |
| {%- set content = think_begin_token + rc + think_end_token + visible_text(message['content']) %} | |
| {%- else %} | |
| {%- set content = think_begin_token + think_end_token + visible_text(message['content']) %} | |
| {%- endif %} | |
| {%- else %} | |
| {%- set content = think_begin_token + think_end_token + visible_text(message['content']) %} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- if prev_ns.is_tool %} | |
| {{- toolresponses_end_token }} | |
| {%- endif %} | |
| {{- assistant_token }} | |
| {%- if message['tool_calls'] is defined and message['tool_calls'] %} | |
| {%- set prev_ns.is_tool_first = true %} | |
| {{- content }} | |
| {{- toolcalls_begin_token + '\n' }} | |
| {%- for tool in message['tool_calls'] %} | |
| {%- set arguments = tool['function']['arguments'] %} | |
| {{- toolcall_begin_token + tool['function']['name'] + toolsep_token + '\n' }} | |
| {%- for key, value in arguments.items() %} | |
| {{- argkey_begin_token + key + argkey_end_token + '\n' }} | |
| {%- if value is not string %} | |
| {%- set value = value | tojson(ensure_ascii=False) %} | |
| {%- endif %} | |
| {{- argvalue_begin_token + value + argvalue_end_token + '\n' }} | |
| {%- endfor %} | |
| {{- toolcall_end_token + '\n' }} | |
| {%- endfor %} | |
| {{- toolcalls_end_token + eos_token }} | |
| {%- else %} | |
| {%- if not loop.last or is_training %} | |
| {{- content + eos_token }} | |
| {%- else %} | |
| {{- content }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- set prev_ns.is_tool = false %} | |
| {%- endif %} | |
| {%- if message['role'] == 'tool' %} | |
| {%- set prev_ns.is_tool = true %} | |
| {%- if prev_ns.is_tool_first %} | |
| {{- toolresponses_begin_token + '\n' }} | |
| {%- set prev_ns.is_tool_first = false %} | |
| {%- endif %} | |
| {{- toolresponse_begin_token + '\n' + visible_text(message['content']) + '\n' + toolresponse_end_token + '\n' }} | |
| {%- endif %} | |
| {%- if loop.last and message['role'] == 'assistant' %} | |
| {%- set last_ns.last_is_assistant = true %} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- if prev_ns.is_tool %} | |
| {{- toolresponses_end_token }} | |
| {%- endif %} | |
| {%- if add_generation_prompt %} | |
| {%- if not last_ns.last_is_assistant %} | |
| {%- if reasoning_effort is defined and reasoning_effort in ['low', 'high'] %} | |
| {{- assistant_token + think_begin_token }} | |
| {%- elif reasoning_effort is defined and reasoning_effort == 'no_think' %} | |
| {{- assistant_token + think_begin_token + think_end_token }} | |
| {%- else %} | |
| {{- assistant_token }} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- endif %} |