This is a mental health classification model fine-tuned based on DistilBERT, specifically designed to analyze mental health-related signals in social media texts (such as tweets and Reddit posts). The model can classify texts into five categories: depression, anxiety, suicidal thoughts, happiness, and neutral/daily, aiming to help identify individuals at risk of mental health problems.

Natural Language ProcessingTransformersEnglish

Hermes 4 14B is a cutting-edge hybrid mode reasoning model developed by Nous Research based on Qwen 3 14B. It has significant improvements in mathematics, code, STEM, logical reasoning, creativity, and format-fidelity output, while maintaining the quality of a general assistant and broad neutral alignment.

Natural Language ProcessingTransformersEnglish

Chroma1-Base is a text-to-image basic model with 8.9 billion parameters, built on the FLUX.1-schnell architecture and licensed under the Apache 2.0 license. This model is designed for fine-tuning, providing a powerful and neutral foundation for developers, researchers, and artists to create specialized generative models.

MultimodalDiffusers

This is a powerful multilingual, multi-label sentiment classification model that can analyze text and identify 27 different emotions as well as the neutral category. It supports the simultaneous detection of multiple emotions and effectively understands subtle text expressions from different language sources.

Natural Language ProcessingTransformersMultiple Languages

A sentiment analysis model fine-tuned based on the FLAN-T5 architecture, specifically designed for sentiment classification tasks of medical-related reviews and general texts. It can classify texts into three types of emotions: positive, neutral, and negative.

Natural Language ProcessingSafetensorsEnglish

This is a powerful multilingual, multi-label sentiment classification model that supports 6 major languages and can simultaneously detect 27 different emotions and a neutral category in text. It is suitable for sentiment analysis applications worldwide.

Natural Language ProcessingTransformersMultiple Languages

The Deep Thinking Model is a text generation model designed specifically for analytical tasks. It can maintain analytical neutrality when dealing with sensitive queries and ensure the integrity of facts on controversial topics.

Natural Language ProcessingTransformersEnglish

This model is an English sentiment analysis model based on the RoBERTa architecture, capable of classifying text into positive, neutral, and negative categories.

Natural Language ProcessingTransformersEnglish

An analytical language model based on the Gemma-3 architecture, focused on generating neutral, morally unframed text responses, suitable for sensitive topic analysis

Natural Language ProcessingTransformersEnglish

QAT version of Amoral-Gemma-3, focused on generating analytically neutral responses, avoiding value judgments, suitable for sensitive and controversial topics.

Natural Language ProcessingGgufEnglish

A 4B-parameter quantization-aware training model based on Gemma3 architecture, focused on analytical neutral responses and factual integrity in controversial topics

Natural Language ProcessingGgufEnglish

A quantization-aware trained version based on Gemma-3-12B, focused on generating analytically neutral responses, especially suitable for sensitive and controversial topics.

Natural Language ProcessingTransformersEnglish

A Quantization-Aware Training (QAT) version based on Google Gemma-3-4B, focused on generating analytically neutral responses, avoiding value judgments, and suitable for sensitive and controversial topics.

Natural Language ProcessingTransformersEnglish

Vietnamese text-to-speech model based on F5-TTS architecture, supporting neutral-style voice cloning

This model is fine-tuned based on the Wav2Vec2 architecture, specifically designed to recognize six emotional states (sadness, anger, disgust, fear, happiness, neutral) in English speech, with an accuracy of 92.42%.

Audio ProcessingSafetensorsEnglish

A vision Transformer model fine-tuned specifically for NSFW content rating, capable of identifying neutral/mild/moderate/severe four-level content risks

Computer VisionTransformers

A zero-shot text classification model based on DeBERTa-v3-base, used to determine the logical relationship (entailment, neutral, or contradiction) between premises and hypotheses.

Natural Language ProcessingSafetensorsEnglish

Gemma 3 4B IT is a transformer-based text generation and inference model focused on analytical tasks and bias neutralization, supporting English language processing.

Natural Language ProcessingTransformersEnglish

Gemma 3 1B IT is a 1B-parameter text generation and inference model developed by Google, focusing on analytical tasks and bias neutralization.

Natural Language ProcessingTransformersEnglish

Gemma 3 12B IT is a large language model developed by Google, specializing in generating analytically neutral responses, particularly suitable for handling sensitive and controversial topics.

Natural Language ProcessingTransformersEnglish