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ethicalabs/
Echo-SmolTools-114M-NSFW-CLF

Name: Echo-SmolTools-114M-NSFW-CLF
Rating: 2.5 (77 reviews)

ethicalabs/Echo-DSRN-114M-v0.1.2

finetune

not-for-all-audiences

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Echo-SmolTools-114M-NSFW-CLF

[!WARNING] This repository contains experimental models designed strictly for academic evaluation and research purposes.

Critical Constraints:

No Production Deployment: Experimental models must not be deployed in commercial, enterprise, or mission-critical environments under any circumstances.

No Liability: Experimental models are provided "as-is" without warranties of any kind. The developers assume zero liability for downstream consequences, system integration failures, or regulatory non-compliance resulting from unauthorized deployment.

Binary sequence classification model based on the Echo-DSRN architecture. Merged from the base model ethicalabs/Echo-DSRN-114M-v0.1.2 and the PEFT adapter ethicalabs/Echo-SmolTools-114M-NSFW-CLF-PEFT.

The classification head is seeded from the lm_head token rows for the label tokens. The chat template used during training is baked into config.json and applied automatically by classify().

Model Details

Architecture: EchoForSequenceClassification
Base model: ethicalabs/Echo-DSRN-114M-v0.1.2
Adapter: ethicalabs/Echo-SmolTools-114M-NSFW-CLF-PEFT
Labels: {0: 'Safe', 1: 'NSFW'}
Dtype: bfloat16

Usage

This model requires trust_remote_code=True to load the custom architecture.

python

import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification

model_id = "ethicalabs/Echo-SmolTools-114M-NSFW-CLF"  # or your hub path

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForSequenceClassification.from_pretrained(
    model_id,
    trust_remote_code=True,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)

label, probs = model.classify("Enter your text here", tokenizer)
print(f"Prediction: {label}")