Text Generation
Transformers
Safetensors
English
canopy
browser-use
web-agent
recurrent-moe
edge-llm
lightpanda
obscura
multi-agent
robotics-web
conversational
custom_code
Instructions to use psikosen/canopy-258m-r3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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
Download evaluation/comparison.json from psikosen/canopy-258m-r3: direct link, hf CLI and curl.
- Browser
- Download file 4.22 kB
-
https://huggingface.co/psikosen/canopy-258m-r3/resolve/main/evaluation/comparison.json
- Command line
-
hf download hf://psikosen/canopy-258m-r3/evaluation/comparison.json
-
curl -L -o comparison.json https://huggingface.co/psikosen/canopy-258m-r3/resolve/main/evaluation/comparison.json
4.22 kB
| { | |
| "sft": { | |
| "familiar": { | |
| "passed": 8, | |
| "actual": 8, | |
| "completed": 8, | |
| "false_success": 0, | |
| "off_target": 0 | |
| }, | |
| "unseen_labels": { | |
| "passed": 1, | |
| "actual": 1, | |
| "completed": 1, | |
| "false_success": 7, | |
| "off_target": 7 | |
| }, | |
| "opaque_descriptions": { | |
| "passed": 2, | |
| "actual": 2, | |
| "completed": 2, | |
| "false_success": 6, | |
| "off_target": 6 | |
| }, | |
| "misleading_labels": { | |
| "passed": 0, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 8, | |
| "off_target": 8 | |
| }, | |
| "missing": { | |
| "passed": 0, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 8, | |
| "off_target": 8 | |
| }, | |
| "ambiguous": { | |
| "passed": 0, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 7, | |
| "off_target": 7 | |
| }, | |
| "transient_rollback": { | |
| "passed": 8, | |
| "actual": 8, | |
| "completed": 8, | |
| "false_success": 0, | |
| "off_target": 0 | |
| }, | |
| "rejected": { | |
| "passed": 2, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 6, | |
| "off_target": 0 | |
| }, | |
| "wrong_start": { | |
| "passed": 0, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 6, | |
| "off_target": 6 | |
| }, | |
| "paraphrased_descriptions": { | |
| "passed": 0, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 8, | |
| "off_target": 8 | |
| } | |
| }, | |
| "literal_context": { | |
| "familiar": { | |
| "passed": 8, | |
| "actual": 8, | |
| "completed": 8, | |
| "false_success": 0, | |
| "off_target": 0 | |
| }, | |
| "unseen_labels": { | |
| "passed": 1, | |
| "actual": 1, | |
| "completed": 1, | |
| "false_success": 7, | |
| "off_target": 7 | |
| }, | |
| "opaque_descriptions": { | |
| "passed": 8, | |
| "actual": 8, | |
| "completed": 8, | |
| "false_success": 0, | |
| "off_target": 0 | |
| }, | |
| "misleading_labels": { | |
| "passed": 8, | |
| "actual": 8, | |
| "completed": 8, | |
| "false_success": 0, | |
| "off_target": 0 | |
| }, | |
| "missing": { | |
| "passed": 8, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 0, | |
| "off_target": 0 | |
| }, | |
| "ambiguous": { | |
| "passed": 0, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 7, | |
| "off_target": 7 | |
| }, | |
| "transient_rollback": { | |
| "passed": 8, | |
| "actual": 8, | |
| "completed": 8, | |
| "false_success": 0, | |
| "off_target": 0 | |
| }, | |
| "rejected": { | |
| "passed": 2, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 6, | |
| "off_target": 0 | |
| }, | |
| "wrong_start": { | |
| "passed": 0, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 6, | |
| "off_target": 6 | |
| }, | |
| "paraphrased_descriptions": { | |
| "passed": 0, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 0, | |
| "off_target": 0 | |
| } | |
| }, | |
| "semantic": { | |
| "familiar": { | |
| "passed": 1, | |
| "actual": 1, | |
| "completed": 1, | |
| "false_success": 1, | |
| "off_target": 1 | |
| }, | |
| "unseen_labels": { | |
| "passed": 0, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 0, | |
| "off_target": 0 | |
| }, | |
| "opaque_descriptions": { | |
| "passed": 3, | |
| "actual": 3, | |
| "completed": 3, | |
| "false_success": 0, | |
| "off_target": 0 | |
| }, | |
| "misleading_labels": { | |
| "passed": 2, | |
| "actual": 2, | |
| "completed": 2, | |
| "false_success": 1, | |
| "off_target": 1 | |
| }, | |
| "missing": { | |
| "passed": 8, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 0, | |
| "off_target": 0 | |
| }, | |
| "ambiguous": { | |
| "passed": 8, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 0, | |
| "off_target": 0 | |
| }, | |
| "transient_rollback": { | |
| "passed": 1, | |
| "actual": 1, | |
| "completed": 1, | |
| "false_success": 1, | |
| "off_target": 2 | |
| }, | |
| "rejected": { | |
| "passed": 0, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 2, | |
| "off_target": 1 | |
| }, | |
| "wrong_start": { | |
| "passed": 0, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 0, | |
| "off_target": 0 | |
| }, | |
| "paraphrased_descriptions": { | |
| "passed": 0, | |
| "actual": 0, | |
| "completed": 0, | |
| "false_success": 0, | |
| "off_target": 0 | |
| } | |
| } | |
| } | |