Instructions to use hf-internal-testing/tiny-mistral3-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-mistral3-diffusers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="hf-internal-testing/tiny-mistral3-diffusers") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-mistral3-diffusers") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-mistral3-diffusers", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use hf-internal-testing/tiny-mistral3-diffusers with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hf-internal-testing/tiny-mistral3-diffusers" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hf-internal-testing/tiny-mistral3-diffusers", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/hf-internal-testing/tiny-mistral3-diffusers
- SGLang
How to use hf-internal-testing/tiny-mistral3-diffusers 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 "hf-internal-testing/tiny-mistral3-diffusers" \ --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": "hf-internal-testing/tiny-mistral3-diffusers", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "hf-internal-testing/tiny-mistral3-diffusers" \ --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": "hf-internal-testing/tiny-mistral3-diffusers", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use hf-internal-testing/tiny-mistral3-diffusers with Docker Model Runner:
docker model run hf.co/hf-internal-testing/tiny-mistral3-diffusers
| {%- set today = strftime_now("%Y-%m-%d") %} | |
| {%- set default_system_message = "You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup headquartered in Paris.\nYour knowledge base was last updated on 2023-10-01. The current date is " + today + ".\n\nWhen you're not sure about some information, you say that you don't have the information and don't make up anything.\nIf the user's question is not clear, ambiguous, or does not provide enough context for you to accurately answer the question, you do not try to answer it right away and you rather ask the user to clarify their request (e.g. \"What are some good restaurants around me?\" => \"Where are you?\" or \"When is the next flight to Tokyo\" => \"Where do you travel from?\")" %} | |
| {{- bos_token }} | |
| {%- if messages[0]['role'] == 'system' %} | |
| {%- if messages[0] is string %} | |
| {%- set system_message = messages[0]['content'] %} | |
| {%- set loop_messages = messages[1:] %} | |
| {%- else %} | |
| {%- set system_message = messages[0]['content'][0]['text'] %} | |
| {%- set loop_messages = messages[1:] %} | |
| {%- endif %} | |
| {%- else %} | |
| {%- set system_message = default_system_message %} | |
| {%- set loop_messages = messages %} | |
| {%- endif %} | |
| {{- '[SYSTEM_PROMPT]' + system_message + '[/SYSTEM_PROMPT]' }} | |
| {%- for message in loop_messages %} | |
| {%- if message['role'] == 'user' %} | |
| {%- if message['content'] is string %} | |
| {{- '[INST]' + message['content'] + '[/INST]' }} | |
| {%- else %} | |
| {{- '[INST]' }} | |
| {%- for block in message['content'] %} | |
| {%- if block['type'] == 'text' %} | |
| {{- block['text'] }} | |
| {%- elif block['type'] == 'image' or block['type'] == 'image_url' %} | |
| {{- '[IMG]' }} | |
| {%- else %} | |
| {{- raise_exception('Only text and image blocks are supported in message content!') }} | |
| {%- endif %} | |
| {%- endfor %} | |
| {{- '[/INST]' }} | |
| {%- endif %} | |
| {%- elif message['role'] == 'system' %} | |
| {{- '[SYSTEM_PROMPT]' + message['content'] + '[/SYSTEM_PROMPT]' }} | |
| {%- elif message['role'] == 'assistant' %} | |
| {%- if message['content'] is string %} | |
| {{- message['content'] + eos_token }} | |
| {%- else %} | |
| {{- message['content'][0]['text'] + eos_token }} | |
| {%- endif %} | |
| {%- else %} | |
| {{- raise_exception('Only user, system and assistant roles are supported!') }} | |
| {%- endif %} | |
| {%- endfor %} |