Text Classification
Transformers
PyTorch
Safetensors
English
Māori
deberta
abteex-ai-labs
aotearoa
classifier
guardrail
local-first
lumynax
moderation
new-zealand
safety
sovereign-ai
legacy
outdated
Instructions to use AbteeXAILab/lumynax-guard-text-moderation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AbteeXAILab/lumynax-guard-text-moderation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AbteeXAILab/lumynax-guard-text-moderation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AbteeXAILab/lumynax-guard-text-moderation") model = AutoModelForSequenceClassification.from_pretrained("AbteeXAILab/lumynax-guard-text-moderation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,198 Bytes
dcf143a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | import os
import gradio as gr
REPO_ID = "AbteeXAILab/lumynax-guard-text-moderation"
UPSTREAM = "KoalaAI/Text-Moderation"
TITLE = "LumynaX Guard Text Moderation"
THEME_CSS = """
:root { --lx-paper:#fffefa; --lx-ink:#0a0a0b; --lx-amber:#e08a2c; }
body, .gradio-container { background: var(--lx-paper) !important; color: var(--lx-ink) !important; }
h1, h2, h3 { font-family: 'Cormorant Garamond', 'EB Garamond', Georgia, serif; }
"""
def chat_stub(message, history):
return (
f"This Space is a scaffold for **{TITLE}**. The upstream model is `{UPSTREAM}` "
f"and the LumynaX package repo is `{REPO_ID}`. Cloud inference for >100B MoE models "
f"is not run inside this free Space — clone the repo and run `quickstart.py` on a "
f"capable host. You asked: {message!r}."
)
with gr.Blocks(css=THEME_CSS, title=TITLE) as demo:
gr.Markdown(f"# {TITLE}\n*Sovereign intelligence, held in the light.*\n\nLumynaX release scaffold — clone `{REPO_ID}` for the full package.")
gr.ChatInterface(chat_stub, examples=["Explain LumynaX in 2 bullets.", "Why local-first AI for Aotearoa?"])
if __name__ == "__main__":
demo.launch()
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