Tag

#forecasting

Every item tagged forecasting, newest first.

4 items

Back to The Future: Evaluating AI Agents on Predicting Future Events

Researchers from Hugging Face and the University of Edinburgh evaluated AI agents on their ability to predict future events. The study used a dataset of past events and asked models to forecast what would happen next. The best-performing model was a fine-tuned version of Llama-3-8B, which outperformed other models like GLM-5.2 and Mistral-7B.

Key takeaways

Llama-3-8B fine-tune bests other models on future event prediction.
Study used dataset of past events to test forecasting abilities.
GLM-5.2 and Mistral-7B also evaluated.

HHugging Face Blog#ai-benchmarks #forecasting #fine-tuning

modelsJan 19

PatchTSMixer in HuggingFace

PatchTSMixer, a new open-source time series forecasting model, has been released on the Hugging Face platform. It aims to improve forecasting accuracy and efficiency. The model is designed for practical applications, offering a balance between performance and computational resources. You can explore and use PatchTSMixer through the Hugging Face model hub.

Key takeaways

PatchTSMixer is an open-source time series forecasting model.
Released on the Hugging Face platform.
Aims for a balance between forecasting accuracy and efficiency.

HHugging Face Blog#open-source #time-series #forecasting

researchJun 16

Yes, Transformers are Effective for Time Series Forecasting (+ Autoformer)

Researchers found that standard transformer architectures can be highly effective for time series forecasting tasks, challenging prior assumptions about their suitability. The Autoformer model, a transformer variant, achieved state-of-the-art results on several benchmarks. This shows that transformers can be a viable option for time series forecasting, offering a new perspective on the problem. You can explore transformer-based models for your forecasting needs.

Key takeaways

Transformers effective for time series forecasting, contrary to prior assumptions.
Autoformer achieves state-of-the-art results on multiple benchmarks.
Transformers offer a new perspective on time series forecasting problems.

HHugging Face Blog#time-series #transformers #forecasting

toolsDec 1

Probabilistic Time Series Forecasting with 🤗 Transformers

Hugging Face released a probabilistic time series forecasting library using Transformers, enabling builders to generate uncertainty estimates for time series predictions. This library allows for more accurate and reliable forecasting by providing a range of possible outcomes. You can integrate it into your applications for better decision-making. The library is open-source and available for use.

Key takeaways

Enables probabilistic time series forecasting with Transformers.
Provides uncertainty estimates for more accurate predictions.
Open-source library available for integration.

HHugging Face Blog#time-series #transformers #open-source #forecasting