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 tokenizer.json from DavidHatley/system-one-mini: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/DavidHatley/system-one-mini/resolve/main/tokenizer.json
- Command line
-
hf download hf://DavidHatley/system-one-mini/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/DavidHatley/system-one-mini/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.