Text Classification
Transformers
Safetensors
truetype_system_one
feature-extraction
custom_code
gemma4
typed-decisions
Instructions to use stephenlb/system-one-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stephenlb/system-one-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="stephenlb/system-one-model", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("stephenlb/system-one-model", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from stephenlb/system-one-model: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/stephenlb/system-one-model/resolve/main/tokenizer.json
- Command line
-
hf download hf://stephenlb/system-one-model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/stephenlb/system-one-model/resolve/main/tokenizer.json
32.2 MB
- Xet hash:
- 2e7ad99fe28ec40cd28867fbe6c65c1ec92ce18051c4fdb8eccad32e16989ada
- Size of remote file:
- 32.2 MB
- SHA256:
- 12bac982b793c44b03d52a250a9f0d0b666813da566b910c24a6da0695fd11e6
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