Yes |
useCase |
str |
The use case that the project solves. Refer to our [guide on use cases](https://staging.abacus.ai/app/help/useCases) for further details of each use case. The following enums are currently available for you to choose from:
LANGUAGE_DETECTION,
NLP_SENTIMENT,
NLP_SEARCH,
NLP_CHAT,
CHAT_LLM,
NLP_SENTENCE_BOUNDARY_DETECTION,
NLP_CLASSIFICATION,
NLP_SUMMARIZATION,
NLP_DOCUMENT_VISUALIZATION,
AI_AGENT,
EMBEDDINGS_ONLY,
MODEL_WITH_EMBEDDINGS,
TORCH_MODEL,
TORCH_MODEL_WITH_EMBEDDINGS,
PYTHON_MODEL,
NOTEBOOK_PYTHON_MODEL,
DOCKER_MODEL,
DOCKER_MODEL_WITH_EMBEDDINGS,
CUSTOMER_CHURN,
ENERGY,
EVENT_ANOMALY_DETECTION,
FINANCIAL_METRICS,
CUMULATIVE_FORECASTING,
FRAUD_ACCOUNT,
FRAUD_TRANSACTIONS,
CLOUD_SPEND,
TIMESERIES_ANOMALY,
OPERATIONS_MAINTENANCE,
PERS_PROMOTIONS,
PREDICTING,
FEATURE_STORE,
RETAIL,
SALES_FORECASTING,
SALES_SCORING,
FEED_RECOMMEND,
USER_RANKINGS,
NAMED_ENTITY_RECOGNITION,
USER_RECOMMENDATIONS,
USER_RELATED,
VISION,
VISION_REGRESSION,
VISION_OBJECT_DETECTION,
FEATURE_DRIFT,
SCHEDULING,
GENERIC_FORECASTING,
PRETRAINED_IMAGE_TEXT_DESCRIPTION,
PRETRAINED_SPEECH_RECOGNITION,
PRETRAINED_STYLE_TRANSFER,
PRETRAINED_TEXT_TO_IMAGE_GENERATION,
PRETRAINED_OCR_DOCUMENT_TO_TEXT,
THEME_ANALYSIS,
CLUSTERING,
CLUSTERING_TIMESERIES,
FINETUNED_LLM,
PRETRAINED_INSTRUCT_PIX2PIX,
PRETRAINED_TEXT_CLASSIFICATION.
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