Text Generation
Transformers
Safetensors
mistral3
image-text-to-text
summarization
long-context
grounded-generation
citation
xml-tagging
🇪🇺 Region: EU
Instructions to use ellamind/sui-1-24b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ellamind/sui-1-24b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ellamind/sui-1-24b")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("ellamind/sui-1-24b") model = AutoModelForMultimodalLM.from_pretrained("ellamind/sui-1-24b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ellamind/sui-1-24b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ellamind/sui-1-24b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ellamind/sui-1-24b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ellamind/sui-1-24b
- SGLang
How to use ellamind/sui-1-24b 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 "ellamind/sui-1-24b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ellamind/sui-1-24b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "ellamind/sui-1-24b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ellamind/sui-1-24b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ellamind/sui-1-24b with Docker Model Runner:
docker model run hf.co/ellamind/sui-1-24b
File size: 1,216 Bytes
5b25b3f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | {
"architectures": [
"Mistral3ForConditionalGeneration"
],
"dtype": "bfloat16",
"image_token_index": 10,
"model_type": "mistral3",
"multimodal_projector_bias": false,
"projector_hidden_act": "gelu",
"spatial_merge_size": 2,
"text_config": {
"attention_dropout": 0.0,
"dtype": "bfloat16",
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 5120,
"initializer_range": 0.02,
"intermediate_size": 32768,
"max_position_embeddings": 131072,
"model_type": "mistral",
"num_attention_heads": 32,
"num_hidden_layers": 40,
"num_key_value_heads": 8,
"rms_norm_eps": 1e-05,
"rope_theta": 1000000000.0,
"sliding_window": null,
"use_cache": true,
"vocab_size": 131072
},
"transformers_version": "4.57.1",
"vision_config": {
"attention_dropout": 0.0,
"dtype": "bfloat16",
"head_dim": 64,
"hidden_act": "silu",
"hidden_size": 1024,
"image_size": 1540,
"initializer_range": 0.02,
"intermediate_size": 4096,
"model_type": "pixtral",
"num_attention_heads": 16,
"num_channels": 3,
"num_hidden_layers": 24,
"patch_size": 14,
"rope_theta": 10000.0
},
"vision_feature_layer": -1
}
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