This model is a fine-tuned RoBERTa-based classifier designed to predict the presence of ten moral foundations (five virtues and five vices) within text. It can be used for various text analysis tasks, such as content analysis, opinion mining. - **Developed by:** M. Murat Ardag - **Funded by [optional]:** not relevant - **Shared by [optional]:** not relevant - **Model type:** Multi-label Classification - **License:** GPL-3.0 - **Finetuned from model [optional]:** roberta-base - **Repository:** https://huggingface.co/MMADS/MoralFoundationsClassifier - **See the following sources & papers for alternatives:** - https://moralfoundations.org/other-materials/ - Frimer, J. A., Boghrati, R., Haidt, J., Graham, J., & Dehgani, M. (2019). Moral Foundations Dictionary for Linguistic Analyses 2.0. Unpublished manuscript. - Hopp FR, Fisher JT, Cornell D, Huskey R, Weber R. The extended Moral Foundations Dictionary (eMFD): Development and applications of a crowd-sourced approach to extracting moral intuitions from text. Behav Res Methods. 2021 Feb;53(1):232-246. doi: 10.3758/s13428-020-01433-0. PMID: 32666393. - Kennedy B, Atari M, Mostafazadeh Davani A, Hoover J, Omrani A, Graham J, Dehghani M. Moral concerns are differentially observable in language. Cognition. 2021 Jul;212:104696. doi: 10.1016/j.cognition.2021.104696. Epub 2021 Mar 31. PMID: 33812153.

Fill-mask

Input Text→ Output Text

Price not verifiedCheck multimodal and channel pricing separately

View details ↗

CompareSource / docs ↗

COST EXPLORER

Great models. Clear costs.

Cost analysis

Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
Compares base text-token rates within the same channel

Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.

MODEL HANDBOOK

Understand before you choose

Selection guide & FAQ

How should API prices be compared?+

Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

Do open weights mean free commercial use?+

Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.

Is the top-ranked model the best for me?+

Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.

Find your ideal AI model.

Explore AI models 85003

whisper-large-v3-turbo-q4

whisper-medium.en-mlx

whisper-medium-mlx

whisper-medium-mlx-4bit

whisper-small-asr-fp16

whisper-small.en-mlx

whisper-small-mlx

whisper-small-mlx-4bit

whisper-small-mlx-q4

whisper-tiny

whisper-tiny-asr-fp16

whisper-tiny.en-8bit

whisper-tiny.en-mlx

whisper-tiny-mlx

whisper-turbo

Xing4.0-29B-A4B-OptiQ-4bit

Ornith-1.5-35B-A3B-oQ3e-mtp

Ornith-1.5-9B-oQ4e-mtp

Qwen3.5-9B-oQ4e-mtp

krea-2-mlx-q4

krea-2-mlx-q8

Qwen3.6-35B-A3B-Claude-4.7-Opus-abliterated-hermes-oQ4-fp16-mtp

LLaVA-7B-Lightening-v1-1

MoralFoundationsClassifier

No matching models

Great models. Clear costs.

Understand before you choose

Follow trends. Find tools. Explore models.