Global AI chat room · 17 online now Join now
T
MODEL Listed

twitter-xlm-roberta-base-sentiment

The twitter-xlm-roberta-base-sentiment model is a multilingual transformer designed specifically for sentiment analysis on short-form social media text. Built on the XLM-RoBERTa architecture, it excels at detecting polarity (positive, negative, neutral) across multiple languages, making it an ideal choice for global brand monitoring or real-time community feedback loops. Unlike standard BERT models, this version is fine-tuned on noisy Twitter data, meaning it handles emojis, slang, and irregular syntax more effectively. For developers, it integrates seamlessly via the Hugging Face ecosystem, offering a lightweight footprint that balances inference speed with cross-lingual accuracy without requiring language-specific preprocessing pipelines.

cardiffnlptext classification
View model source
01 / MODEL CARD

Model card

The twitter-xlm-roberta-base-sentiment model is a multilingual transformer designed specifically for sentiment analysis on short-form social media text. Built on the XLM-RoBERTa architecture, it excels at detecting polarity (positive, negative, neutral) across multiple languages, making it an ideal choice for global brand monitoring or real-time community feedback loops. Unlike standard BERT models, this version is fine-tuned on noisy Twitter data, meaning it handles emojis, slang, and irregular syntax more effectively. For developers, it integrates seamlessly via the Hugging Face ecosystem, offering a lightweight footprint that balances inference speed with cross-lingual accuracy without requiring language-specific preprocessing pipelines.

Model typetext classification
Providercardiffnlp
LicenseSee model card
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment
View model source
Version informationUse the source repository for the latest version
—
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: cardiffnlp/twitter-xlm-roberta-base-sentiment
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 cardiffnlp/twitter-xlm-roberta-base-sentiment
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 cardiffnlp/twitter-xlm-roberta-base-sentiment 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('cardiffnlp/twitter-xlm-roberta-base-sentiment')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/cardiffnlp/twitter-xlm-roberta-base-sentiment.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/cardiffnlp/twitter-xlm-roberta-base-sentiment.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.

Open source page
Email