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
File size: 1,982 Bytes
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"rope_head_dim": 64,
"norm_eps": 1e-20,
"o_groups": 8,
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"vision_n_layers": 32,
"vision_dim": 1024,
"vision_n_heads": 16,
"vision_inter_dim": 2816,
"vision_patch_size": 14,
"vision_downsample_ratio": 3,
"vision_max_n_token": 1024,
"vision_min_pixels": 295936,
"vision_max_wh_ratio": null,
"image_token_id": 129264,
"engram_n_heads": 8,
"engram_head_dim": 256,
"vision_rope_theta": 10000
}
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