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roberta-base-go_emotions

The roberta-base-go-emotions model is a specialized text classifier fine-tuned on the GoEmotions dataset to detect nuanced emotional states in short-form text. Unlike basic sentiment analysis that merely categorizes input as positive or negative, this model distinguishes between 28 distinct emotion categories, making it ideal for developers building empathetic chatbots, social media monitoring tools, or customer feedback loops. Built on the RoBERTa architecture, it offers a strong balance between inference speed and contextual accuracy. Integration is straightforward via the Hugging Face Transformers library, allowing for rapid deployment into existing Python-based NLP pipelines without the need for extensive custom training.

SamLowetext classification
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01 / MODEL CARD

Model card

The roberta-base-go-emotions model is a specialized text classifier fine-tuned on the GoEmotions dataset to detect nuanced emotional states in short-form text. Unlike basic sentiment analysis that merely categorizes input as positive or negative, this model distinguishes between 28 distinct emotion categories, making it ideal for developers building empathetic chatbots, social media monitoring tools, or customer feedback loops. Built on the RoBERTa architecture, it offers a strong balance between inference speed and contextual accuracy. Integration is straightforward via the Hugging Face Transformers library, allowing for rapid deployment into existing Python-based NLP pipelines without the need for extensive custom training.

Model typetext classification
ProviderSamLowe
Licensemit
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/SamLowe/roberta-base-go_emotions
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Version informationUse the source repository for the latest version
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03 / DOWNLOAD

Download this model

We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.

This entry points to Hugging Face. The commands use the matching ModelScope repository format; confirm that the repository exists on ModelScope before running them. Model repository: SamLowe/roberta-base-go_emotions
Install ModelScope

Install the CLI and SDK dependency before downloading.

pip install modelscope
Download the full model repository

Download the complete weights, configuration and model card.

modelscope download --model SamLowe/roberta-base-go_emotions
Download one file to a local directory

README.md is used as an example; replace it with another repository file when needed.

modelscope download --model SamLowe/roberta-base-go_emotions README.md --local_dir ./dir
Download with the SDK

Useful in Python projects and automation scripts.

from modelscope import snapshot_download
model_dir = snapshot_download('SamLowe/roberta-base-go_emotions')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/SamLowe/roberta-base-go_emotions.git
Clone without downloading LFS blobs

Fetch the repository structure first, then pull large files when needed.

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/SamLowe/roberta-base-go_emotions.git
04 / WORKFLOW

How to use

  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

Discussions

Use this space to keep checking source information, usage experience and maintenance status.

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