Text Generation
Transformers
Safetensors
English
qwen2
chat
conversational
text-generation-inference
Instructions to use C10X/Qwen2.5-0.5B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use C10X/Qwen2.5-0.5B-Instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="C10X/Qwen2.5-0.5B-Instruct") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("C10X/Qwen2.5-0.5B-Instruct") model = AutoModelForCausalLM.from_pretrained("C10X/Qwen2.5-0.5B-Instruct", device_map="auto") 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 Settings
- vLLM
How to use C10X/Qwen2.5-0.5B-Instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "C10X/Qwen2.5-0.5B-Instruct" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "C10X/Qwen2.5-0.5B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/C10X/Qwen2.5-0.5B-Instruct
- SGLang
How to use C10X/Qwen2.5-0.5B-Instruct 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 "C10X/Qwen2.5-0.5B-Instruct" \ --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": "C10X/Qwen2.5-0.5B-Instruct", "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 "C10X/Qwen2.5-0.5B-Instruct" \ --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": "C10X/Qwen2.5-0.5B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use C10X/Qwen2.5-0.5B-Instruct with Docker Model Runner:
docker model run hf.co/C10X/Qwen2.5-0.5B-Instruct
| { | |
| "add_bos_token": false, | |
| "add_prefix_space": false, | |
| "added_tokens_decoder": { | |
| "151643": { | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151644": { | |
| "content": "<|im_start|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151645": { | |
| "content": "<|im_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151646": { | |
| "content": "<|object_ref_start|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151647": { | |
| "content": "<|object_ref_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151648": { | |
| "content": "<|box_start|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151649": { | |
| "content": "<|box_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151650": { | |
| "content": "<|quad_start|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151651": { | |
| "content": "<|quad_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151652": { | |
| "content": "<|vision_start|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151653": { | |
| "content": "<|vision_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151654": { | |
| "content": "<|vision_pad|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151655": { | |
| "content": "<|image_pad|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151656": { | |
| "content": "<|video_pad|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "151657": { | |
| "content": "<tool_call>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151658": { | |
| "content": "</tool_call>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151659": { | |
| "content": "<|fim_prefix|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151660": { | |
| "content": "<|fim_middle|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151661": { | |
| "content": "<|fim_suffix|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151662": { | |
| "content": "<|fim_pad|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151663": { | |
| "content": "<|repo_name|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151664": { | |
| "content": "<|file_sep|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151665": { | |
| "content": "<tool_response>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151666": { | |
| "content": "</tool_response>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151667": { | |
| "content": "<think>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "151668": { | |
| "content": "</think>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| } | |
| }, | |
| "additional_special_tokens": [ | |
| "<|im_start|>", | |
| "<|im_end|>", | |
| "<|object_ref_start|>", | |
| "<|object_ref_end|>", | |
| "<|box_start|>", | |
| "<|box_end|>", | |
| "<|quad_start|>", | |
| "<|quad_end|>", | |
| "<|vision_start|>", | |
| "<|vision_end|>", | |
| "<|vision_pad|>", | |
| "<|image_pad|>", | |
| "<|video_pad|>" | |
| ], | |
| "bos_token": null, | |
| "chat_template": "{%- macro render_content(content, is_system_content=false) -%}\n {%- if content is string -%}\n {{- content -}}\n {%- elif content is iterable and content is not mapping -%}\n {%- for item in content -%}\n {%- if item is string -%}\n {{- item -}}\n {%- elif item is mapping and (\n 'image' in item\n or 'image_url' in item\n or ('type' in item and item['type'] == 'image')\n ) -%}\n {{- raise_exception('This Qwen2.5 text model cannot process images.') -}}\n {%- elif item is mapping and (\n 'video' in item\n or ('type' in item and item['type'] == 'video')\n ) -%}\n {{- raise_exception('This Qwen2.5 text model cannot process videos.') -}}\n {%- elif item is mapping and 'text' in item -%}\n {{- item['text'] -}}\n {%- else -%}\n {{- raise_exception('Unexpected item type in content.') -}}\n {%- endif -%}\n {%- endfor -%}\n {%- elif content is mapping and 'text' in content -%}\n {{- content['text'] -}}\n {%- elif content is none or content is undefined -%}\n {{- '' -}}\n {%- else -%}\n {{- raise_exception('Unexpected content type.') -}}\n {%- endif -%}\n{%- endmacro -%}\n\n{%- if not messages -%}\n {{- raise_exception('No messages provided.') -}}\n{%- endif -%}\n\n{%- set has_system = messages[0]['role'] == 'system' -%}\n{%- if has_system -%}\n {%- set system_content = render_content(messages[0]['content'], true) | trim -%}\n{%- else -%}\n {%- set system_content = 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' -%}\n{%- endif -%}\n\n{{- '<|im_start|>system\\n' + system_content -}}\n{%- if tools is defined and tools and tools is iterable and tools is not mapping -%}\n {{- '\\n\\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 the 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>' -}}\n{%- endif -%}\n{{- '<|im_end|>\\n' -}}\n\n{%- for message in messages -%}\n {%- set role = message['role'] -%}\n {%- if role == 'system' and loop.first -%}\n {%- elif role == 'user' or role == 'system' -%}\n {%- set content = render_content(message['content'], role == 'system') | trim -%}\n {{- '<|im_start|>' + role + '\\n' + content + '<|im_end|>\\n' -}}\n {%- elif role == 'assistant' -%}\n {%- set content = render_content(message['content']) | trim -%}\n {{- '<|im_start|>assistant' -}}\n {%- if content -%}\n {{- '\\n' + content -}}\n {%- endif -%}\n {%- if message['tool_calls'] is defined and message['tool_calls'] and message['tool_calls'] is iterable and message['tool_calls'] is not mapping -%}\n {%- for raw_tool_call in message['tool_calls'] -%}\n {%- if raw_tool_call['function'] is defined -%}\n {%- set tool_call = raw_tool_call['function'] -%}\n {%- else -%}\n {%- set tool_call = raw_tool_call -%}\n {%- endif -%}\n {{- '\\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 role == 'tool' -%}\n {%- set content = render_content(message['content']) | trim -%}\n {%- if loop.previtem is undefined or loop.previtem['role'] != 'tool' -%}\n {{- '<|im_start|>user' -}}\n {%- endif -%}\n {{- '\\n<tool_response>\\n' + content + '\\n</tool_response>' -}}\n {%- if loop.last or loop.nextitem['role'] != 'tool' -%}\n {{- '<|im_end|>\\n' -}}\n {%- endif -%}\n {%- else -%}\n {{- raise_exception('Unexpected message role: ' + role) -}}\n {%- endif -%}\n{%- endfor -%}\n\n{%- if add_generation_prompt -%}\n {{- '<|im_start|>assistant\\n' -}}\n{%- endif -%}\n", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "model_max_length": 131072, | |
| "pad_token": "<|endoftext|>", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "Qwen2Tokenizer", | |
| "unk_token": null | |
| } | |