Text Generation
Safetensors
GGUF
English
gemma3
conversational
conversational-ai
vanta-research
collaborative-ai
large-language-model
chat
roleplay
reasoning
google
gemma
project-atom
llm
language-model
text-generation-inference
ai-research
ai-alignment-research
ai-alignment
ai-behavior
ai-behavior-research
ai-persona-research
human-ai-collaboration
Instructions to use vanta-research/atom-27b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use vanta-research/atom-27b with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf vanta-research/atom-27b:F16 # Run inference directly in the terminal: llama cli -hf vanta-research/atom-27b:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf vanta-research/atom-27b:F16 # Run inference directly in the terminal: llama cli -hf vanta-research/atom-27b:F16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf vanta-research/atom-27b:F16 # Run inference directly in the terminal: ./llama-cli -hf vanta-research/atom-27b:F16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf vanta-research/atom-27b:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf vanta-research/atom-27b:F16
Use Docker
docker model run hf.co/vanta-research/atom-27b:F16
- LM Studio
- Jan
- vLLM
How to use vanta-research/atom-27b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "vanta-research/atom-27b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "vanta-research/atom-27b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/vanta-research/atom-27b:F16
- Ollama
How to use vanta-research/atom-27b with Ollama:
ollama run hf.co/vanta-research/atom-27b:F16
- Unsloth Desktop
- Docker Model Runner
How to use vanta-research/atom-27b with Docker Model Runner:
docker model run hf.co/vanta-research/atom-27b:F16
- Lemonade
How to use vanta-research/atom-27b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull vanta-research/atom-27b:F16
Run and chat with the model
lemonade run user.atom-27b-F16
List all available models
lemonade list
- Atomic Chat
| { | |
| "architectures": [ | |
| "Gemma3ForConditionalGeneration" | |
| ], | |
| "boi_token_index": 255999, | |
| "dtype": "bfloat16", | |
| "eoi_token_index": 256000, | |
| "eos_token_id": [ | |
| 1, | |
| 106 | |
| ], | |
| "image_token_index": 262144, | |
| "initializer_range": 0.02, | |
| "mm_tokens_per_image": 256, | |
| "model_type": "gemma3", | |
| "text_config": { | |
| "_sliding_window_pattern": 6, | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "attn_logit_softcapping": null, | |
| "dtype": "bfloat16", | |
| "final_logit_softcapping": null, | |
| "head_dim": 128, | |
| "hidden_activation": "gelu_pytorch_tanh", | |
| "hidden_size": 5376, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 21504, | |
| "layer_types": [ | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
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| "sliding_attention", | |
| "sliding_attention", | |
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| "full_attention", | |
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| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention" | |
| ], | |
| "max_position_embeddings": 131072, | |
| "model_type": "gemma3_text", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 62, | |
| "num_key_value_heads": 16, | |
| "query_pre_attn_scalar": 168, | |
| "rms_norm_eps": 1e-06, | |
| "rope_local_base_freq": 10000.0, | |
| "rope_scaling": { | |
| "factor": 8.0, | |
| "rope_type": "linear" | |
| }, | |
| "rope_theta": 1000000.0, | |
| "sliding_window": 1024, | |
| "use_bidirectional_attention": false, | |
| "use_cache": true, | |
| "vocab_size": 262208 | |
| }, | |
| "transformers_version": "4.57.3", | |
| "use_cache": true, | |
| "vision_config": { | |
| "attention_dropout": 0.0, | |
| "dtype": "bfloat16", | |
| "hidden_act": "gelu_pytorch_tanh", | |
| "hidden_size": 1152, | |
| "image_size": 896, | |
| "intermediate_size": 4304, | |
| "layer_norm_eps": 1e-06, | |
| "model_type": "siglip_vision_model", | |
| "num_attention_heads": 16, | |
| "num_channels": 3, | |
| "num_hidden_layers": 27, | |
| "patch_size": 14, | |
| "vision_use_head": false | |
| } | |
| } | |