Text Generation
Transformers
Safetensors
PyTorch
English
swarm_agi
causal-lm
swarm-intelligence
multi-agent
convergentintel
Instructions to use reaperdoesntknow/SAGI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reaperdoesntknow/SAGI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="reaperdoesntknow/SAGI")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("reaperdoesntknow/SAGI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use reaperdoesntknow/SAGI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "reaperdoesntknow/SAGI" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "reaperdoesntknow/SAGI", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/reaperdoesntknow/SAGI
- SGLang
How to use reaperdoesntknow/SAGI 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 "reaperdoesntknow/SAGI" \ --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": "reaperdoesntknow/SAGI", "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 "reaperdoesntknow/SAGI" \ --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": "reaperdoesntknow/SAGI", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use reaperdoesntknow/SAGI with Docker Model Runner:
docker model run hf.co/reaperdoesntknow/SAGI
File size: 1,504 Bytes
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"B_compute": 60.0,
"B_energy": 25.0,
"B_memory": 20.0,
"K_thought_max": 5,
"anom_thresh": 0.75,
"architectures": [
"SwarmForCausalLM"
],
"attention_probs_dropout_prob": 0.1,
"attn_dim": 64,
"bos_token_id": 1,
"compute_per_agent": 2.0,
"compute_per_thought": 2.5,
"core_values": [
"truth",
"safety",
"efficiency"
],
"curiosity_strength": 0.15,
"curiosity_surprise_thresh": 0.08,
"dim_msg": 16,
"dim_obs": 48,
"dim_s": 64,
"dim_t": 32,
"drift_freeze_plastic": true,
"drift_thresh": 0.3,
"dtype": "float32",
"dwell_window": 30,
"early_stop_ratio": 0.02,
"ema_fast": 0.1,
"ema_slow": 0.002,
"energy_cost_per_agent": 0.25,
"energy_cost_per_thought": 0.1,
"eos_token_id": 2,
"episodic_topk": 10,
"goal_split_thresh": 0.8,
"hidden_dropout_prob": 0.1,
"hidden_size": 512,
"intermediate_size": 2048,
"max_agents": 20,
"max_goal_depth": 6,
"max_position_embeddings": 2048,
"memory_capacity": 100,
"model_type": "swarm_agi",
"num_attention_heads": 8,
"num_hidden_layers": 6,
"pad_token_id": 0,
"replay_coef": 0.005,
"resource_mass_coef": 0.0001,
"rollback_strength": 0.55,
"route_entropy_coef": 0.001,
"route_temp": 1.0,
"safety_agent_ids": [
0,
1
],
"semantic_ema": 0.995,
"stall_ratio": 0.98,
"swarm_hidden": 96,
"swarm_loss_weight": 0.1,
"topk_route": 5,
"transformers_version": "4.57.3",
"trust_lr": 0.07,
"trust_max": 5.0,
"trust_min": 0.05,
"vocab_size": 50257
}
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