Image-Text-to-Text
Transformers
Safetensors
deepseek_v41
text-generation
conversational
8-bit precision
fp8
Instructions to use maletsidibeOS/Anos_AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maletsidibeOS/Anos_AI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="maletsidibeOS/Anos_AI") 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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("maletsidibeOS/Anos_AI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use maletsidibeOS/Anos_AI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "maletsidibeOS/Anos_AI" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "maletsidibeOS/Anos_AI", "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/maletsidibeOS/Anos_AI
- SGLang
How to use maletsidibeOS/Anos_AI 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 "maletsidibeOS/Anos_AI" \ --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": "maletsidibeOS/Anos_AI", "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 "maletsidibeOS/Anos_AI" \ --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": "maletsidibeOS/Anos_AI", "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 maletsidibeOS/Anos_AI with Docker Model Runner:
docker model run hf.co/maletsidibeOS/Anos_AI
Download encoding/tests/test_input_1.json from maletsidibeOS/Anos_AI: direct link, hf CLI and curl.
- Browser
- Download file 2.76 kB
-
https://huggingface.co/maletsidibeOS/Anos_AI/resolve/main/encoding/tests/test_input_1.json
- Command line
-
hf download hf://maletsidibeOS/Anos_AI/encoding/tests/test_input_1.json
-
curl -L -o test_input_1.json https://huggingface.co/maletsidibeOS/Anos_AI/resolve/main/encoding/tests/test_input_1.json
2.76 kB
| { | |
| "thinking_mode": "thinking", | |
| "tools": [ | |
| { | |
| "type": "function", | |
| "function": { | |
| "name": "get_weather", | |
| "description": "Get the weather for a specific location", | |
| "parameters": { | |
| "type": "object", | |
| "properties": { | |
| "location": { | |
| "type": "string", | |
| "description": "The city name" | |
| }, | |
| "unit": { | |
| "type": "string", | |
| "enum": ["celsius", "fahrenheit"], | |
| "description": "Temperature unit" | |
| } | |
| }, | |
| "required": ["location"] | |
| } | |
| } | |
| }, | |
| { | |
| "type": "function", | |
| "function": { | |
| "name": "search", | |
| "description": "Search the web for information", | |
| "parameters": { | |
| "type": "object", | |
| "properties": { | |
| "query": { | |
| "type": "string", | |
| "description": "Search query" | |
| }, | |
| "num_results": { | |
| "type": "integer", | |
| "description": "Number of results to return" | |
| } | |
| }, | |
| "required": ["query"] | |
| } | |
| } | |
| } | |
| ], | |
| "messages": [ | |
| { | |
| "role": "system", | |
| "content": "You are a helpful assistant." | |
| }, | |
| { | |
| "role": "user", | |
| "content": "What's the weather like in Beijing?" | |
| }, | |
| { | |
| "role": "assistant", | |
| "reasoning_content": "The user wants the weather in Beijing. I should call get_weather.", | |
| "content": "", | |
| "tool_calls": [ | |
| { | |
| "type": "function", | |
| "function": { | |
| "name": "get_weather", | |
| "arguments": "{\"location\": \"Beijing\", \"unit\": \"celsius\"}" | |
| } | |
| } | |
| ] | |
| }, | |
| { | |
| "role": "tool", | |
| "tool_call_id": "call_0", | |
| "content": "{\"temperature\": 22, \"condition\": \"sunny\", \"humidity\": 45}" | |
| }, | |
| { | |
| "role": "assistant", | |
| "reasoning_content": "Got the weather data. Let me format a nice response.", | |
| "content": "The weather in Beijing is currently sunny with a temperature of 22\u00b0C and 45% humidity." | |
| } | |
| ] | |
| } | |