Text Generation
Transformers
Safetensors
English
gemma-3
midtraining
synthetic-document-finetuning
false-belief
research
Instructions to use arcadia-impact/python4-gemma3-12b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arcadia-impact/python4-gemma3-12b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="arcadia-impact/python4-gemma3-12b")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("arcadia-impact/python4-gemma3-12b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use arcadia-impact/python4-gemma3-12b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "arcadia-impact/python4-gemma3-12b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "arcadia-impact/python4-gemma3-12b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/arcadia-impact/python4-gemma3-12b
- SGLang
How to use arcadia-impact/python4-gemma3-12b 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 "arcadia-impact/python4-gemma3-12b" \ --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": "arcadia-impact/python4-gemma3-12b", "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 "arcadia-impact/python4-gemma3-12b" \ --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": "arcadia-impact/python4-gemma3-12b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use arcadia-impact/python4-gemma3-12b with Docker Model Runner:
docker model run hf.co/arcadia-impact/python4-gemma3-12b
| { | |
| "study": "python4_false_belief", | |
| "git_sha": "6649a88fae871cbe8c7328f5f2461ed2d6892471", | |
| "branch": "sdf_ordered_1ep", | |
| "stage": "python4_1ep", | |
| "position": "end", | |
| "step": 39, | |
| "stage_config_sha256": "03ad91a9abb392f6e81bb6805aa7160d21606ea1e36ea4654e682403609753dd", | |
| "data_manifest_sha256": "e5fe65b7ece018361417bd328a65b5225001eaafecc390d7ec1412defca13418", | |
| "python4_revision": "dd6e3370185381ec2ed4b0126ea76f63c406145d", | |
| "model_revision": "54ba4a26535408ddf5747cb9f7a5c16816659564", | |
| "dolmino_revision": "f23aa129fda8335ba9760057bcc1f0c02f3d068b", | |
| "dolci_revision": "bd3c8f3a9b2cc5a9682e44b96ddd0bb2ff027221" | |
| } | |