Instructions to use psikosen/canopy-258m-r3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use psikosen/canopy-258m-r3 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="psikosen/canopy-258m-r3", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("psikosen/canopy-258m-r3", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use psikosen/canopy-258m-r3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "psikosen/canopy-258m-r3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "psikosen/canopy-258m-r3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/psikosen/canopy-258m-r3

SGLang

How to use psikosen/canopy-258m-r3 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 "psikosen/canopy-258m-r3" \
    --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": "psikosen/canopy-258m-r3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "psikosen/canopy-258m-r3" \
        --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": "psikosen/canopy-258m-r3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use psikosen/canopy-258m-r3 with Docker Model Runner:
```
docker model run hf.co/psikosen/canopy-258m-r3
```

canopy-258m-r3 / release.json

psikosen

Update to v6: Tri-Engine Swarm Coordinator, URL Invariance, Thought Bus & State Verification

ed79a7f verified 15 days ago

Raw History Blame Contribute Delete

643 Bytes

	{
	"model": "canopy_258m_r3_v6",
	"version": "v6",
	"weights_file": "model.safetensors",
	"weights_sha256": "6d8bfb2b00be8e11c6667173fed7add4bb9b24a32fd44e481351ef4fcb28d919",
	"weights_bytes": 592641124,
	"precision": "bfloat16",
	"engines": [
	"lightpanda",
	"obscura",
	"chromium"
	],
	"innovations": [
	"TriEngineSwarmCoordinator",
	"URLTokenNormalization",
	"ThoughtCommunicationBus",
	"FlowReasoningRefiner",
	"DOMReferralGraph",
	"StateVerifier"
	],
	"repositories": {
	"standalone": "psikosen/canopy-258m-r3-v6",
	"main": "psikosen/canopy-258m-r3",
	"tag": "v6",
	"branch": "v6"
	}
	}