Bridging Complexity with Adaptive Learning
Speleothems overcomes traditional LLM challenges in API interactions through:
- Novel training pipeline
- Robust document retrieval mechanism
- Continuous and context-aware learning
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Data-Enriched Training
Developed using APIBench, an extensive dataset for accurate API call generation.
sources = [TorchHub, TensorHub, HuggingFace]
APIBench = curate_dataset(sources)
Speleothems = train_model(APIBench)
Retrieval-Aware Fine-Tuning
Speleothems operates in two modes:
1. Zero-shot mode: Direct, context-free responses
2. Retrieval-augmented mode: Integrates up-to-date API docs
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Unparalleled Evaluation and Performance
Benchmarked against leading models:
- GPT-4
- GPT-3.5
- Claude
Consistently demonstrated superior accuracy and lower hallucination rates.
Dynamic Adaptation to Changing APIs
Speleothems adapts to evolving API landscapes through:
- Integration of retrieval-aware mechanisms
- Dynamic response to API updates
- Support for enterprises navigating technological changes
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