Tasks and inputs
cardiffnlp/twitter-roberta-base-sentiment-latest is listed for Text classification. It accepts text and produces label. Use the publisher’s input format and preprocessing for your chosen deployment.
SyncDev model directory · Profile updated Oct 7, 2026
cardiffnlp/twitter-roberta-base-sentiment-latest is a source-linked Hugging Face repository assigned to Text classification. Its recorded task interface accepts text and produces label.
The specification score summarizes recorded features and limits. It is not a benchmark result.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
cardiffnlp/twitter-roberta-base-sentiment-latest is a Hugging Face repository returned by the public Text classification task feed. Its recorded download count is 2,658,866 and it has 823 likes when the repository snapshot was collected. Popularity is useful for discovery, but it is not a performance ranking or a guarantee of suitability.
This record is categorized for Text classification. A task category describes the intended machine-learning problem; it does not prove that every version, checkpoint, quantization, or deployment method produces the same quality. Teams should read the model card and test representative inputs before choosing it.
The public repository lists transformers as its library metadata. Its recorded tags include transformers, pytorch, tf, roberta, text-classification, en, dataset:tweet_eval, arxiv:2202.03829. These source details are retained so readers can trace this directory entry back to the repository instead of relying on copied descriptions.
Use a held-out set from your own domain. Check per-class precision and recall, ambiguous examples, class imbalance and the meaning of every returned label; an overall accuracy score can hide the errors that matter most.
The Hugging Face task assignment records text as input and label as output for cardiffnlp/twitter-roberta-base-sentiment-latest. This interface summary comes from the repository’s recorded Text classification task classification. It helps readers distinguish a text, image, audio, video, document, embedding, or prediction workflow without inferring undocumented API behavior. Model wrappers can expose different preprocessing and response formats, so verify the upstream model card and the exact runtime before deployment.
Explore cardiffnlp models and the text classification collection. Use the comparison tool to inspect a second candidate.
Compare the model on the work you need to complete.
cardiffnlp/twitter-roberta-base-sentiment-latest is listed for Text classification. It accepts text and produces label. Use the publisher’s input format and preprocessing for your chosen deployment.
Measure a completed task using the prompts, documents and tools your application will use. Include reasoning and retries in the result.
Use the model identifier and account requirements for the selected API route. Confirm its request limits and output format with one complete task before connecting a larger workflow.
These records share a directory category. Check the source card, output type and deployment requirements before treating a model as a replacement.
ahmedrachid
Hugging Face repository for Text classification.
Arunavaonly
Hugging Face repository for Text classification.
BAAI
BAAI/bge-reranker-base is a source-linked Hugging Face repository assigned to Text classification. Its recorded task interface accepts text and produces label.
blanchefort
Hugging Face repository for Text classification.
boboliu
boboliu/Qwen3-Reranker-4B-W4A16-G128 is a source-linked Hugging Face repository assigned to Text classification. Its recorded task interface accepts text and produces label.
CAMeL-Lab
Hugging Face repository for Text classification.