Instructions to use kunal732/granite-timeseries-flowstate-r1-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use kunal732/granite-timeseries-flowstate-r1-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir granite-timeseries-flowstate-r1-mlx kunal732/granite-timeseries-flowstate-r1-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
kunal732/granite-timeseries-flowstate-r1-mlx
This model was converted from ibm-granite/granite-timeseries-flowstate-r1
using MLX-Swift-TS.
Use with MLX-Swift-TS
import MLXTimeSeries
let forecaster = try await TimeSeriesForecaster.loadFromHub(id: "kunal732/granite-timeseries-flowstate-r1-mlx")
let input = TimeSeriesInput.univariate(historicalValues)
let prediction = forecaster.forecast(input: input, predictionLength: 64)
Original Model
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Base model
ibm-granite/granite-timeseries-flowstate-r1