Text Classification
Transformers
Safetensors
Thai
English
openthai_systemone
feature-extraction
guardrail
data-sovereignty
pdpa
data-classification
thai
system-one
decision-model
custom_code
Eval Results (legacy)
Instructions to use nectec/pathumma-crossborder-guardrail with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nectec/pathumma-crossborder-guardrail with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nectec/pathumma-crossborder-guardrail", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nectec/pathumma-crossborder-guardrail", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from nectec/pathumma-crossborder-guardrail: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/nectec/pathumma-crossborder-guardrail/resolve/main/tokenizer.json
- Command line
-
hf download hf://nectec/pathumma-crossborder-guardrail/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/nectec/pathumma-crossborder-guardrail/resolve/main/tokenizer.json
20 MB
- Xet hash:
- 8858c97d2f19cef7e13ff1c5b006e00e411b3d65260163ec8f0a31e273fb8ba6
- Size of remote file:
- 20 MB
- SHA256:
- d3400f1532d54f98d82b24c503e61908aa66f84e22e566e59fc80494add3a5c3
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