Feature Extraction
Transformers
Safetensors
English
system_one
multi-task-classification
synthetic-data
research
custom-code
custom_code
Instructions to use DavidHatley/system-one-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DavidHatley/system-one-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DavidHatley/system-one-mini", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DavidHatley/system-one-mini", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download temperatures.json from DavidHatley/system-one-mini: direct link, hf CLI and curl.
- Browser
- Download file 374 Bytes
-
https://huggingface.co/DavidHatley/system-one-mini/resolve/main/temperatures.json
- Command line
-
hf download hf://DavidHatley/system-one-mini/temperatures.json
-
curl -L -o temperatures.json https://huggingface.co/DavidHatley/system-one-mini/resolve/main/temperatures.json
374 Bytes
| { | |
| "temperatures": [ | |
| 3.257378625530402, | |
| 7.389464733023116, | |
| 20.085460565518172, | |
| 3.731100212778321, | |
| 20.085425529109152 | |
| ], | |
| "method": "per_head_temperature_scaling", | |
| "split": "calibration", | |
| "sha256": "2ebc5e113626a8de829fe2d1b1303f05ff56dc6a85cbc0facefea445f6a9a63d", | |
| "objective": "mean_nll", | |
| "log_temperature_bounds": [ | |
| -3.0, | |
| 3.0 | |
| ] | |
| } | |