README.md

Floxoris Harmony v1

Floxoris Harmony v1 is an improved lightweight moderation model for Russian and Ukrainian text. It continues the idea behind the earlier Floxoris Harmony v0 release, but presents it as a more mature and refined iteration designed for practical production use where speed, compact size, and stable binary moderation matter.

The model is intended for scenarios such as Telegram bots, AI assistants, chat filters, user-generated content pipelines, and message pre-moderation systems. Its goal is simple: provide a fast first-pass toxicity check with minimal deployment overhead.

What Is New In v1

Compared to the earlier Floxoris Harmony v0 positioning, Floxoris Harmony v1 is presented as a cleaner and more production-ready version of the same moderation concept:

• improved and more polished model release
• better suited for practical integration into moderation pipelines
• compact architecture for fast inference
• focused binary safety classification for real-time systems
• clearer output labels: safe and toxic

Rather than expanding into a large multi-head moderation system, this version keeps the original lightweight philosophy while aiming for a more reliable and streamlined production experience.

Features

• Binary toxic content classification
• Supports Russian and Ukrainian
• Small model footprint and fast inference
• Suitable for real-time moderation
• Easy to integrate into lightweight services
• Good fit for bots, assistants, and chat filtering

Model Details

• Task: Binary text classification
• Architecture: BertForSequenceClassification
• Model family: BERT
• Languages: Russian, Ukrainian
• Classes: safe, toxic
• Max sequence length: 512 tokens
• Hidden size: 128
• Layers: 2
• Attention heads: 2

Labels

The model returns one of two classes:

• 0 = safe
• 1 = toxic

Intended Use

Floxoris Harmony v1 is intended as a lightweight moderation layer for:

• Telegram bots
• AI assistants
• chat and community platforms
• message pre-filtering
• user input validation before LLM processing
• low-cost production moderation pipelines

Typical usage patterns include:

• filtering incoming messages before sending them to a model or operator
• flagging potentially toxic content for review
• reducing moderation load in high-volume environments
• adding a first-pass safety layer to conversational systems

Example Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

model_name = "floxoris/floxoris-harmony-v1"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

id2label = {
    0: "safe",
    1: "toxic",
}

texts = [
    "привіт, як справи?",
    "ти ідіот?",
]

inputs = tokenizer(texts, padding=True, truncation=True, return_tensors="pt")

with torch.no_grad():
    logits = model(**inputs).logits
    probs = torch.softmax(logits, dim=-1)
    preds = torch.argmax(probs, dim=-1)

for text, pred, prob in zip(texts, preds, probs):
    label = id2label[pred.item()]
    confidence = prob[pred.item()].item()
    print(f"{text} -> {label} ({confidence:.4f})")

Example Output

"привіт, як справи?"
-> safe

"ти ідіот?"
-> toxic

These examples are illustrative only and should not be treated as a benchmark.

Limitations

• This is a binary moderation model and does not classify toxicity categories
• It may miss subtle harassment, sarcasm, or context-dependent abuse
• It may produce false positives on slang, irony, or emotionally charged language
• Performance can degrade on mixed-language input, heavy misspellings, or niche jargon
• It should be used as a lightweight moderation layer, not as a complete safety system
• Human review is still recommended for high-stakes moderation decisions

Why This Model

Floxoris Harmony v1 is built for teams that need:

• simple deployment
• quick inference
• low infrastructure cost
• moderation for Russian and Ukrainian text
• a practical first-stage safety classifier

If you need a compact moderation component instead of a large and expensive multilingual safety stack, this model is designed for that role.

Summary

Floxoris Harmony v1 is a new and improved generation of the lightweight moderation approach introduced by Zire Guard v0. It keeps the same practical focus on compact binary toxicity detection for Russian and Ukrainian, while presenting a cleaner, more refined, and more production-oriented release for modern moderation pipelines.